Cybersecurity crimes in cryptocurrency exchanges (2009–2024) and emerging quantum threats: the largest unified dataset of CEX and DEX incidents

Abstract

Cryptocurrency exchanges are integral to the digital asset economy; however, their rapid growth has been accompanied by recurrent high-impact cyberattacks that erode trust and inflict substantial losses. Guided by the PRISMA-ScR framework, this review systematically screened peer-reviewed and industry sources to construct a validated dataset of 220 major incidents (2009–2024) across centralized (CEX) and decentralized (DEX) exchanges. We classify attack vectors, analyze repeated high-impact patterns, and identify systemic vulnerabilities spanning cryptographic mechanisms and exchange infrastructure. Across CEX platforms, four of ten identified attack types accounted for 62 of the 80 incidents and approximately $1.764 billion in losses (42.1% of the $4.191 billion CEX total). Across DEX platforms, five of eighteen attack types were responsible for 120 of 140 incidents, totaling $3.755 billion (87.3% of the $4.303 billion DEX total). The overall losses sum to $8.494 billion across 220 incidents (80 CEX; 140 DEX). Repeated vectors comprised 182/220 incidents and $5.519 billion (65.0%) of losses, dominated by wallet/key compromise (78 incidents; $2.394 billion) and DEX system/server/protocol exploits (56 incidents; $1.939 billion); these two classes account for 134/182 repeated incidents (79.1%) and $4.333 billion (78.5%) of repeated losses. We examine the susceptibility of cryptographic defenses to emerging quantum adversaries and assess the exchange readiness for post-quantum threats. This study is the first to systematically compile and quantitatively analyze cybercrime incidents affecting both centralized and decentralized cryptocurrency exchanges in a unified dataset, enabling unprecedented comparability of systemic risks with actionable insights for cybersecurity researchers, regulators, and exchange operators seeking quantum-safe infrastructure evolution.

1 Introduction

Cryptocurrencies and cryptocurrency exchange platforms (CExPs), encompassing both centralized (CEX) and decentralized (DEX) exchanges, are intrinsically linked, with exchanges providing the essential infrastructure that facilitates transactions and drives global adoption (Kim and Lee, 2018). In this study, we used CExPs when referring to exchanges generically and CEX/DEX when distinguishing between the two types. Cryptocurrency has become a global phenomenon in the 21st century (Corbet et al., 2019b) and has attracted increasing levels of cybercrime, particularly against CExPs, which serve as the primary conduits for cryptocurrency transactions (Vital, 2022; Manimuthu et al., 2019; Connolly and Wall, 2019). Despite the challenges of transacting outside formal venues, the sustained growth in the acceptance of cryptocurrencies as an alternative to fiat currency is underpinned by the security and trust provided by exchanges (Bucko et al., 2015; Kawai et al., 2023). In practice, CExPs expand cryptocurrency usability by offering user-friendly rails for liquidity, rapid settlement, and broad accessibility (Oliva et al., 2019; Arli et al., 2021) (Supplementary Tables S1, S2).

Since 2009, at least 220 high-impact cyberattacks have been reported in exchanges, with a total of approximately $8.494 billion (Chainalysis, 2022; Vidal-Tomás, 2022; Giechaskiel, 2016). These incidents span both centralized exchanges (CEXs) and decentralized exchanges (DEXs), the two dominant architectures in the ecosystem, where CEXs are custodial order-book venues and DEXs are non-custodial smart-contract protocols (e.g., AMMs or on-chain order books). Together, CEX and DEX represent the core infrastructure of the global cryptocurrency economy, serving over 500 million users by 2024 and facilitating the majority of cryptocurrency liquidity and settlement (IMARC Group, 2023; Jani, 2018). Other venues, such as OTC desks, P2P platforms, and custodial brokers, exist, but their transaction volumes and user bases remain marginal compared to CEX and DEX. Hence, this study focused on these two dominant exchange types.

Exchanges are integral to digital finance, enabling the buying, selling, and conversion of assets such as Bitcoin and Ethereum (Marella et al., 2021; Rejeb et al., 2021), and they play a central role in liquidity formation, price discovery, and on-/off-ramping between fiat and crypto (Chutipat et al., 2023). As of May 2024, over 500 exchanges were operating globally (CoinMarketCap, 2023; Future Market Insights, 2023; Triple-A Technologies Pte. Ltd., 2024). Binance led spot and derivatives activities, often processing tens of billions of dollars in daily volume across markets, while other major venues, including Coinbase, Bybit, and Kraken, contributed materially to market liquidity and user trust (Cambridge Centre for Alternative Finance, 2017a).

By late 2024, the global crypto market capitalization was approximately $2 trillion (Chainalysis, 2023b). Annual trading volumes further highlight the market’s scale: in 2024 alone, the top-15 centralized spot exchanges (CEXs) processed $18.8 trillion; the top-10 decentralized exchanges (DEXs) handled $1.76 trillion; and derivatives trading volumes were even higher, reaching $58.5 trillion on the top-10 centralized exchanges offering perpetual contracts and $2.9 trillion on their decentralized counterparts (CCData, 2025; DefiLlama, 2025a; DefiLlama, 2025b; DefiLlama, 2025c). In parallel, user adoption is expected to expand to an estimated 600 million global crypto users by the end of 2024 (IMARC Group, 2023; Jani, 2018). The growing participation of both retail and institutional investors further amplifies the systemic importance of crypto exchanges (Coinpedia, 2023; Chainalysis, 2023a).

The same characteristics that make exchanges efficient, high-throughput, deep liquidity, and global access also increase their attractiveness to attackers (Al-Amri, 2019; Oosthoek, 2021; Ahuja, 2023; Basilan, 2024). As the value of assets under custody increases, there is an incentive for sophisticated attacks (Rot and Blaicke, 2019). The pseudonymity and cross-jurisdictional nature of blockchain flows complicate asset tracing and recovery, whereas weaknesses in wallet/key management, authentication, and transaction-validation pipelines remain persistent pressure points (Crystal Blockchain, 2024b; Hedge with Crypto, 2024; Crystal Blockchain, 2024a; Sigurdsson et al., 2020; Adamik and Kosta, 2019; Shaji et al., 2022). Historically, attacks have included phishing, credential theft, malware, insider abuse, protocol and smart contract exploits, and large-scale DDoS events that exploit the gaps in both operational controls and cryptographic guardrails (Feder et al., 2017; Alia, 2014). In 2024 alone, over ten major breaches were recorded, with losses exceeding $1.018 billion (Berry, 2022); a notable example is the WazirX incident of July 2024 (approximately $230million) (Crystal Intelligence, 2024). These incidents further reveal critical weaknesses in wallet security (Erinle et al., 2023), authentication protocols, and transaction validation mechanisms (Homoliak and Perešíni, 2024), and continue to drive regulatory responses (e.g., KYC/AML regimes) across jurisdictions (Mohsin, 2022; Mateen, 2023; Ruiz et al., 2022; Zhou et al., 2023; Soana, 2024), which often address symptoms rather than root causes in the system architecture.

An additional risk acceleration is the prospective impact of quantum computing (Faruk et al., 2022; Bergstrom, 2024). Algorithms such as Shor and Grover threaten the hardness assumptions of widely deployed schemes (RSA and ECC) with implications for key custody, signatures, and consensus security (Fernández-Caramés, 2020; Easa et al., 2023; Vasavi and Latha, 2019). Given the “harvest-now, decrypt-later” risk, the key material exfiltrated today can be decrypted by future quantum adversaries, thereby increasing the urgency for migration to post-quantum cryptography (PQC) (Roy, 2019; Thanalakshmi et al., 2023). Leading PQC families, including lattice-based KEMs and signatures, hash-based signatures, and multivariate schemes, offer candidates for hardening key exchanges, authentication, and protocol design.

Against this backdrop, prior reviews have often conflated exchange-related incidents with wallet-only breaches or broader DeFi exploits, limiting comparability and obscuring systemic vulnerabilities specific to exchange infrastructure. Wallet-only breaches are often driven by end-user errors, such as private key mismanagement or phishing, whereas exchange breaches expose deeper architectural flaws in custodial systems, smart contracts and liquidity protocols. By isolating exchange-specific incidents, this study provides the first PRISMA-ScR scoping review that systematically maps systemic risks across CEX and DEX platforms. Furthermore, the 220 incidents analyzed not only revealed recurrent attack vectors but also highlighted the fragility of cryptographic mechanisms that face existential threats from quantum-capable adversaries. Linking historical breach patterns to quantum-era risks strengthens the case for urgent migration to post-quantum cryptography in exchange infrastructure. This dual focus, systemic cyber risk, and quantum-era cryptographic fragility position the study to inform both immediate resilience strategies and long-term PQC migration pathways.

Despite the growing body of research on blockchain security, two critical research gaps remain unaddressed. First, the literature lacks a unified, longitudinal synthesis that isolates exchange-specific cyber incidents and compares systemic vulnerabilities across CEX and DEX architectures. Second, very few studies integrate post-quantum cryptographic readiness into the analysis of exchange security, even though quantum threats directly challenge the cryptographic foundations of trading, custody, and consensus. Addressing these interlinked gaps is essential to align historical evidence with the technological transition toward quantum-resilient infrastructures and to guide both academic inquiry and regulatory preparedness in the digital-asset domain.

This review critically investigates the evolving cybersecurity dynamics of cryptocurrency exchanges by examining both their historical vulnerabilities and their readiness for quantum-era threats. In direct response to the identified research gaps, the study pursues two overarching aims: first, to provide a unified, exchange-specific synthesis that compares systemic vulnerabilities across centralized (CEX) and decentralized (DEX) platforms; and second, to evaluate the preparedness of exchange cryptographic infrastructures for post-quantum migration. Specifically, we (i) conduct a systematic review and classification of repeated high-impact incidents involving exchanges from 2009 to 2024, (ii) identify common vulnerabilities and recurring attack vectors that have compromised exchange security, (iii) assess quantum-era risks to current cryptographic infrastructures, and (iv) offer actionable post-quantum–ready recommendations for exchanges and policymakers (Navarro, 2019). Unless otherwise stated, dollar amounts are USD (nominal, not inflation-adjusted), and reported volumes refer to calendar year 2024 benchmarks (CCData, 2025; DefiLlama, 2025a; DefiLlama, 2025b; DefiLlama, 2025c).

Beyond addressing these gaps, this study contributes to both theory and practice. Theoretically, it extends the understanding of cybersecurity resilience in digital-asset infrastructures by providing a longitudinal, exchange-specific taxonomy of high-impact incidents. Methodologically, it demonstrates how a PRISMA-ScR framework can be adapted to synthesize technical breach data across heterogeneous blockchain ecosystems. Managerially and for policy, the findings generate actionable insights for exchange operators, cybersecurity agencies, and regulators seeking to strengthen governance standards and guide post-quantum transition strategies. Collectively, these contributions position the review as a reference baseline for future empirical, regulatory, and cryptographic research on exchange security.

The remainder of this paper is organized as follows: Section 2 reviews the background and related studies. Section 3 details the PRISMA-ScR scoping methodology and data extraction pipeline. Section 4 briefly introduces exchange platforms (CEX/DEX), security/architecture, and frames the high-impact crimes. Section 5 presents the incident corpus and results (taxonomy, trends, cross-platform comparisons, losses, and repeated vectors). Section 6 analyzes the attack techniques and patterns, whereas Section 7 emphasizes classical cryptographic vulnerabilities and defenses. Section 8 expands on post-quantum threats and the PQC readiness of the CExPs. Section 9 discusses the synthesis of the results, limitations, research gaps, and recommendations. Finally, Section 10 concludes the study.

2 Background and related work

Although many publications discuss cryptocurrencies and related crimes, relatively few have analyzed the detailed mechanics of crimes against cryptocurrency exchange platforms (CExPs). Therefore, we review the literature most relevant to exchange security, emphasizing recent studies (2018–2024), which are summarized in Table 1.

Rising concerns over CExP security have driven studies on scams, cyberattacks, authentication, and cryptography, aimed at improving transparency, accountability, and resilience against both classical and quantum-enabled threats (Shalini and Santhi, 2019). The literature is synthesized below by theme:

2.1 Cryptocurrency exchange vulnerabilities and attacks

Vasek and Moore classified scams into four categories: fraudulent exchanges, Ponzi schemes, mining scams, and scam wallets, highlighting definitional challenges and the absence of systematic classifications (Vasek and Moore, 2018; Nabilou, 2020). Trozze et al. identified 29 types of fraud across academic and gray sources, underscoring research growth and the need for clearer definitions and collaboration (Trozze et al., 2022). Bartoletti et al. propose automated scam detection but note noisy labels and lack of a universal taxonomy (Bartoletti et al., 2021). Sigurdsson et al. (2020) and Chohan (2022) examined vulnerabilities (DDoS, phishing, social engineering, malleability, and double spending) paired with cost-raising countermeasures. Feder et al. analyzed the impact of DDoS on Bitcoin exchanges (Feder et al., 2017), whereas Abhishta et al. found that the activity typically normalizes within a day (Arli et al., 2021). Vasek et al. further highlighted malware and extortion, noting that theft declines after security upgrades (Vasek et al., 2014). Gottipati (2020) designed a defense model using Runtime Application Self-Protection (RASP) and Hardware Security Modules (HSMs), but focused only on centralized exchanges. Smith and Kahn De Saint Guilhem et al. (2020) proposed a composable framework for key exchange against man-in-the-middle attacks, although there is a lack of deployment evidence.

Gap: These studies propose defenses but none compile a longitudinal, unified dataset of high-impact crimes across both CEX and DEX.

2.2 Authentication and security in cryptocurrency exchanges

Chenchev et al. (2021) surveyed wallet authentication methods such as passwords, biometrics, MFA, blockchain-based methods, and stress persistent weaknesses. Homoliak and Perešíni, 2024 introduced “k-factor” authentication using threshold cryptography but focused narrowly on wallets. Doe and Smith Zhang et al. (2024) propose a privacy-preserving, threshold authentication framework, though centralization and scalability remain issues. Alghamdi et al. (2024) show multimodal biometric fusion reduces attack success rates but overlook governance and regulation. Goh et al. (2022) developed a multimodal fingerprint/iris framework with Adaptive Feature Hashing, offering unlinkability but lacking exchange-scale testing. Brown et al. (2020) integrate biometrics with blockchain and ML but omit stress tests and compliance considerations. Vasavi and Latha (2019) explored multimodal fusion with RSA, achieving accuracy but at the cost of latency.

Gap: Authentication research is fragmented and not systematically tied to large-scale CEX/DEX breach data.

2.3 Encryption techniques and their challenges

Olaiya et al. (2024) surveyed symmetric, asymmetric, hybrid, and homomorphic encryption and noted the performance, key management, and integration trade-offs, whereas advanced paradigms (homomorphic and PQC) remain early in deployment. However, empirical benchmarks and migration strategies are lacking.

Gap: Few works map encryption weaknesses directly to the high-impact vectors observed in CEX/DEX incidents.

2.4 Quantum threats and post-quantum cryptography (PQC)

Shor-type attacks expose RSA/ECDH/ECDSA, prompting studies on PQC for exchanges (Gill et al., 2022). Chen (2024) advocated for PQC signatures (Dilithium) but omitted broader PQC families or hybrid migration paths. Saha et al. integrate lattice- and hash-based PQC into blockchain, showing performance gains but neglecting multivariate/code-based families and live deployment (Saha et al., 2023). Other studies have highlighted PQC’s importance of PQC against Shor and Grover (Rosch-Grace and Straub, 2021). Chen Dharminder et al. (2023) proposed an RLWE-based protocol with good performance, but it lacked privacy features and large-scale optimization. Yi (2022) applies lattice-based cryptography to SIoT, improving key exchange, but exchange-scale feasibility is untested.

Gap: PQC studies focus on design but rarely connect with empirical exchange breach data which our dataset provides this missing link.

2.5 Consumer trust and accountability in exchanges

Marella et al. (2021), Arli et al. (2021) showed that trust recovery requires compensation, not apologies. Chohan (2022) called for transparency, monitoring, and accountability.

Gap: Trust research seldom links erosion directly to the repeated scale of CEX/DEX incidents.

2.6 Regulatory measures and global standards

Bucko et al. (2015) discussed certification bodies (e.g., C4) and global harmonization efforts (Xiong and Luo, 2024; Caliskan, 2022).

Gap: Regulatory work proposes frameworks but lacks quantitative grounding in the historical trajectory of high-impact incidents.

Synthesis of Gaps: Collectively, prior research covers scams, authentication, encryption, PQC, trust, and regulation. However, there is no comprehensive longitudinal dataset of high-impact incidents across the CEX and DEX. This study addresses this gap by compiling the largest unified dataset of 220 exchange-specific incidents (2009–2024), enabling cross-architecture comparisons, identification of repeated vectors, and contextualization of quantum-era risks (Table 2).

3 Review methodology

Figure 1 presents an overview of the PRISMA-ScR–guided methodology adopted in this study, illustrating the sequential stages from scoping and article selection to eligibility screening, data extraction, incident verification, and synthesis of results.

FIGURE 1

3.1 Scoping review

Scoping reviews systematically map the breadth and nature of research on established or emerging topics using an iterative, structured approach (Sarkis-Onofre et al., 2021; Mattos et al., 2023). This study aimed to analyze, evaluate, and classify existing studies on crimes against cryptocurrency exchange platforms (CExPs). We reviewed both peer-reviewed and gray literature sources (Vergara-Merino et al., 2021) on cybercrimes against exchanges (Souza et al., 2022). The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR) guidelines, with eligibility criteria defined a priori to ensure scope alignment and reproducibility (Tricco et al., 2016). In this study, “crime” is defined as any act (fraud, hacking, theft, or cyber-attack) committed to gain financial or asset benefits from exchanges.

3.2 Article selection methods

We conducted a scoping review of the academic and gray literature on crimes against cryptocurrency exchange platforms, focusing on repeated high-impact attack vectors affecting centralized (CEX) and decentralized (DEX) exchanges between 2009 and 2024. This review adhered to the PRISMA-ScR guidelines (Munn et al., 2018; Munn et al. 2022). Eligibility was determined based on publication type, language, topical relevance, and direct linkage to exchange securities.

3.3 Study selection

Searches were performed in the Web of Science, Scopus, and Google Scholar databases until 31 December 2024. In total, we identified 735 records (630 academic and 105 Gy literature articles). Duplicates were removed in Microsoft Excel using a two-pass procedure (pass 1: DOI-normalized exact match; pass 2: title-normalized + year for records without a DOI). All unique titles and abstracts were screened.

Academic literature. Of the 630 screened academic records, 301 underwent full-text reviews. After screening, 214 articles met all inclusion criteria and were retained, while 87 were excluded.

Gray literature. Of the 105 Gy records screened, 95 proceeded to full-text eligibility, 78 were finally included, and 17 were excluded during the title/abstract screening.

A total of 292 sources (214 academic and 78 Gy) met the inclusion criteria and were included in this review. The authors independently screened the studies, and disagreements were resolved through discussion. As shown in Figure 2, these counts align with the PRISMA-ScR flow diagram, ensuring full transparency at each stage.

FIGURE 2

3.4 Eligibility criteria

Although cryptocurrency security breaches occur across wallets, tokens, and broader DeFi protocols, this review explicitly focuses on exchange-centric incidents (centralized exchanges (CEX) and decentralized exchanges (DEX)). Wallet-only breaches were excluded because they primarily involve user-side vulnerabilities (e.g., private key mismanagement and phishing) rather than systemic flaws in the exchange infrastructure. Including such cases would blur the scope and reduce the comparability of the aggregated loss data. By restricting the inclusion to exchange-focused incidents, the review maintains analytic consistency with PRISMA-ScR and ensures that the findings remain directly relevant to exchange resilience, regulatory oversight, and post-quantum preparedness.

Only studies written in English were included. Eligible sources comprised peer-reviewed journal articles, conference papers, and formal reports (e.g., CERT advisories, technical white papers, and documented incident post-mortems) classified as gray literature. Editorials, opinion pieces, marketing materials, newsletters, and news articles were excluded from the study.

Topically, the included studies had to address crimes against CExPs (CEX or DEX) or their direct security posture (e.g., wallet/key management within exchanges, smart contract exchange logic, or bridges/oracles when tied to exchange incidents). We also included studies on quantum threats relevant to exchanges when they explicitly connected PQ/quantum risks (e.g., RSA/ECC compromise, Grover-related symmetric considerations) to exchange infrastructures or incident classes.

3.5 Search strategy

The complete database-specific queries are listed in Supplementary Table S3. Because Google Scholar restricts queries to approximately 256 characters, we executed the query set as multiple searches using the quoted phrases to control drift. The search was restricted to records published between January 2009 and December 2024. For gray literature, we restricted the results to English-language PDF files to ensure reproducibility. Both academic and gray searches included peer-reviewed articles, conference papers, theses, monographs, and technical reports. Duplicates across databases were systematically resolved using the two-pass procedure described above. Disagreements at the full-text inclusion stage were resolved by consensus.

3.6 Procedure for data extraction

As presented in Supplementary Table S4, we meticulously retrieved pertinent information for the scoping review by conducting structured searches across the Web of Science, Scopus, and Google Scholar. Multiple search strings were combined to extract relevant records. Google Scholar, which offers broader indexing coverage, provided the most robust results among the databases consulted.

3.7 Incident verification and coding

As shown in Figure 1, all steps were executed sequentially to ensure methodological transparency and reproducibility. Each incident was cross-verified across at least two independent sources such as exchange post-mortems, auditor reports, and regulatory filings to ensure authenticity and avoid double counting. Incidents were classified as major if the reported or independently confirmed financial loss exceeded USD 50,000 or caused service disruption exceeding 24 h. A standardized coding sheet was developed to capture the following variables: year, exchange type (CEX/DEX), loss magnitude, attack vector, recurrence status, and cryptographic relevance. Two reviewers independently coded all incidents, and intercoder agreement was assessed using percentage concordance (97%). Any discrepancies were resolved by discussion to maintain reliability and alignment with PRISMA-ScR transparency principles.

3.8 Scoping review results

Using the PRISMA-ScR framework (Stovold et al., 2014; Page et al., 2021), our systematic review process identified 735 sources (630 academic and 105 Gy). After removing duplicates and applying title/abstract and full-text screening, we included 292 sources (214 academic, 78 Gy). As shown in Figure 2, these numbers are aligned with the PRISMA-ScR flow diagram.

4 Brief history of cryptocurrency exchanges and cybersecurity crimes

4.1 Historical overview of cryptocurrency exchanges

When Bitcoin (BTC) was launched in 2009, it had no fixed market value and could only be obtained through mining or high-risk trades (Nakamoto, 2009; Wang et al., 2024b). The early exchange history was marked by fraud, hacks, and legal challenges, laying the groundwork for today’s global infrastructure (Al-Amri, 2019; Caliskan, 2021). Currently, more than 600 exchanges operate globally (Bartoletti et al., 2021; CoinMarketCap, 2025). Early transactions, such as those between Hal Finney and Satoshi Nakamoto on 12 January 2009, were experimental (Ruoti et al., 2020).

Before the 2008 Bitcoin white paper and 2009 Genesis Block Nakamoto (2009), trading occurred informally via forums or IRC and relied on trust. The first exchange, bitcoinmarket. com, was launched in March 2010 (Cryptohopper, 2023; World.org, 2023). By 2011, Mt. Gox had become the largest exchange and the site of the first major cybercrime (CoinDesk, 2023; Morin et al., 2023; Dimpfl and Flad, 2020). Hackers exploited a compromised hot wallet, crashing BTC prices from $17 to nearly zero and leaking user data. Despite this, Mt. Gox still handled 70% of global Bitcoin trade in 2013 before registering with FinCEN. Over time, exchanges have evolved with a greater focus on user experience and security (Gayathri et al., 2023; Fang et al., 2022). Leading platforms have introduced secure trading procedures (Watorek et al., 2020), although the regulatory burdens vary across jurisdictions (Mohsin, 2022).

4.1.1 CEX and DEX platforms

Cryptocurrency exchanges are privately run platforms in which users trade cryptocurrencies against fiat currencies or other assets (Czapliński et al., 2019; Bhaskar and Chuen, 2024). Orders can be executed at set prices or spot rates (Bentov et al., 2019; Keller and Scholz, 2019). Two main models exist: centralized (CEX) and decentralized (DEX) (Takahashi et al., 2019). Both aim to ensure liquidity, security, and rapid settlement, with some exchanges evolving into full trading platforms that offer analytical tools.

4.1.2 Centralized exchanges (CEXs)

In CEXs, a single authority manages the accounts and transactions (Zhou et al., 2022). They function like digital stock markets, earning fees and commissions (Patashkova et al., 2021). Its advantages include high liquidity, faster fund recovery, and selective asset listings. Drawbacks include custodial risks, centralized storage of sensitive data, and a history of price manipulation. The major CEXs include Binance, Bybit, Coinbase, Kraken, and KuCoin (Fu et al., 2022; Eigelshoven et al., 2021).

4.1.3 Decentralized exchanges (DEXs)

DEXs operate on distributed ledger technology without a central authority (Jain et al., 2021; Victor and Weintraud, 2021). Users control their keys and trade directly from their wallets, bypassing intermediaries and KYC requirements (Xu et al., 2023). They typically allow swaps within the same blockchain, such as Ethereum-based tokens. Its strengths include full custody, lower fees, higher privacy, and distributed hosting (Patel et al., 2019; Tripathi et al., 2023). Its weaknesses include low liquidity and limited interoperability. Examples include Uniswap, PancakeSwap, dYdX, and Kyber (Corbet et al., 2019a).

4.2 Overview of exchange security

4.2.1 Exchange architecture

Exchanges integrate multiple layers to enable asset trading, such as Bitcoin and Ethereum (Marella et al., 2021; Navarro, 2019). Their design combines security and efficiency across interconnected components. Supplementary Table S8 summarizes the layers, definitions, threats and defenses.

5 Cybersecurity incidents in cryptocurrency exchanges

From 2009 to 2024, cryptocurrency exchange platforms reported at least 220 high-impact security incidents, including hacks, thefts, scams, fraud, and breaches, arising from exploited vulnerabilities (Scharfman, 2023; Murugappan et al., 2023). The quantified losses across these incidents totaled $8.494 billion from 2009 to 2024 (Chainalysis, 2022; Chainalysis 2023b; Charoenwong et al., 2022; Chainalysis Team, 2024). As of 25 August 2023, the ecosystem comprised 16,500 cryptocurrencies and 600 active cryptocurrency exchanges (CoinMarketCap, 2023; CoinMarketCap, 2025), for which the 24-h trading volume was approximately billion, with 68 million crypto-wallet owners and 430 million users (Bergstrom, 2024; Paganini, 2018). The scale and liquidity of these markets have made exchanges attractive targets, leading to repeated high-impact attacks and losses for users and platforms, thereby eroding confidence in cryptocurrencies as a fiat alternative worldwide (Hamrick et al., 2021). To the best of our knowledge, this study compiles the largest unified dataset of exchange-only crimes, covering both CEX and DEX incidents from 2009 to 2024. Unlike prior reviews that mixed exchanges with wallets or generalized DeFi exploits, our focus isolates exchange-specific breaches, enabling an unprecedented comparison of systemic risks across architectures.

Supplementary Table S1 (CEX) and S2 (DEX) outline the full set of 220 major incidents with a cumulative loss of $8.494 billion from 2009 to 2024 (Aspris et al., 2021; Manthovani et al., 2023). Of these, 80 incidents involved CEX and 140 involved DEX (Navamani, 2021).

5.1 Incidents classification

Tables 3, 5 summarize the incident taxonomy and counts for CEX and DEX respectively; the full record of 220 incidents (CEX 80; DEX 140) is provided in Supplementary Table S1 (CEX) and S2 (DEX).

5.1.1 Corpus and sources

We compiled incidents from 2009–2024 using peer-reviewed studies and preprints, auditor/forensic and blockchain-analytics reports, official exchange disclosures and post-mortems, regulatory/court materials, reputable industry media, and security research blogs. This comprehensive multi-source triangulation ensures that the resulting dataset is not only the broadest compiled to date but also systematically validated and de-duplicated, distinguishing it from earlier fragmented surveys. The specific sources that populated the database were as follows: Corbet et al. (2019b); Manimuthu et al. (2019); Connolly and Wall (2019); Bucko et al. (2015); Chainalysis (2022); Vidal-Tomás (2022); Marella et al. (2021); Chohan (2022); Chainalysis (2023b); Chainalysis (2023a); Oosthoek (2021); Anita (2019); Bartoletti et al. (2021); Crystal Blockchain (2024b); Hedge with Crypto (2024); Crystal Blockchain (2024a); Sigurdsson et al. (2020); Feder et al. (2017); Berry (2022); Crystal Intelligence (2024); Navarro (2019); Shalini and Santhi (2019); Trozze et al. (2022); Vasek et al. (2014); CoinMarketCap (2025); Bit2Me Academy (2016); Cryptohopper (2023); World.org (2023); CoinDesk (2023); Fu et al. (2022); Eigelshoven et al. (2021); Corbet et al. (2019a); Charoenwong et al. (2022); Chainalysis Team (2024); Hamrick et al. (2021); Aspris et al. (2021); Manthovani et al. (2023); Abhishta et al. (2019); Panjwani (2023); Bhusal (2021); Blockchain (2022); Minto (2022); Badaw et al. (2020); Sengupta et al. (2020); Nabilou (2020); Patel (2022); Horch et al. (2022); Conti et al. (2018); Xia (2020); Oosthoek et al. (2020); Kasera (2020); Tandon and Nayyar (2019); Astrakhantseva et al. (2021); Shevchenko et al. (2022).

5.1.2 Inclusion and exclusion

We included exchange-platform security incidents (CEX or DEX) with (i) a clearly described compromise vector and (ii) a documented or conservatively estimated their financial impacts. We excluded non-exchange scams with no platform compromise, purely off-chain fraud that does not involve exchange infrastructure or duplicates.

5.1.3 Screening and de-duplication

All candidate items were screened and then de-duplicated by matching venue + date/time window + transaction or On-chain evidence and narrative details. Conflicting loss figures were reconciled by preferring primary disclosures and multi-source concordance, and unresolved ranges were conservatively recorded. This process yielded 220 unique incidents.

5.1.4 Normalization and coding

For each incident we coded: platform type (CEX/DEX), venue, date (UTC), region, attack vector (mapped to the 10-vector CEX and 18-vector DEX taxonomies), loss amount (USD; normalized at the time of reporting), and citation set. Ambiguous geography is tagged as unknown/global. The resulting database underlies all the figures and tables in §5.1.7.1–§5.1.7.6.

5.1.5 Focus on repeated high-impact vectors

From this corpus, we flagged vectors that recurred more than four times and caused losses exceeding $50,000 per incident (excluding non-property crimes). Applying this dual threshold ensures an analytical focus on patterns that are both persistent and financially material while filtering out one-off or low-impact breaches. These repeated high-impact records (CEX top-4; DEX top-5) drive the comparative analyses and the bar charts in §5.1.7.5–5.1.7.6, including the cross-platform private key (CEX + DEX) aggregate (78 incidents; B). This approach, consistent with incident analysis practices in breach reporting and cybercrime research (Shevchenko et al., 2022; Chainalysis, 2023a), allowed for the first rigorous identification of recurrent and high-impact attack vectors across both CEX and DEX. This provides a level of longitudinal granularity and cross-platform comparability that has previously been absent from the literature.

5.1.6 Data generation and curation

The curated incident lists for CEX (Supplementary Table S1; 2009–2024) and DEX (Supplementary Table S2; 2014–2024) constituted the canonical dataset used in this study. Each record includes the event date, venue, platform type, region, attack vector (mapped to the CEX 10-vector/DEX 18-vector taxonomies), loss amount (USD), and source citations. All figures and tables in §5.1.7.1–§5.1.7.6 are reproducible from these two supplementary tables by grouped aggregation over the vector, platform, year, and region fields. Tables 3, 5 define the taxonomies used to construct the summaries, and any total reported in the text (e.g., private key (CEX + DEX) = 78 incidents; B) can be recomputed directly from S1+S2 under these mappings. The complete source list for the dataset is provided in the citations above, and the full 220-incident inventory is presented in Supplementary Tables S1, S2.

5.1.7 Incident results: taxonomy, trends, insights, and impact (2009–2024)

5.1.7.1 Crimes on centralized exchanges (2009–2024)

As summarized in Table 3; Supplementary Table S1, we identified 80 major CEX incidents between 2009 and 2024. Our taxonomy comprises ten attack vectors, including hot wallet/private key compromise, compromised systems/servers, insider exploits, data leaks, and phishing via fake sites. Less frequent categories included protocol/implementation vulnerabilities and 2FA bypass. In aggregate, the quantified CEX losses totaled $4.191 billion; the top four vectors account for 62 of 80 incidents and approximately $1.764 billion (42.1%) of losses (Hong, 2019; Abhishta et al., 2019) (see Table 7 for aggregate losses and Table 4 for vector frequencies). Among the ten identified vectors, hacking/unauthorized access to hot wallets was the most prevalent (Panjwani, 2023; Bhusal, 2021), with 39 of the 80 incidents (nearly 50%). Internal mistakes have a low recurrence rate, whereas compromised servers and hot-wallet access remain persistent vulnerabilities. In 2022, the largest CEX loss was the FTX unauthorized transaction incident, exceeding $400M (Fu et al., 2022; Sigalos, 2023).

5.1.7.2 Crimes on decentralized exchanges (2009–2024)

As summarized in Table 5; Supplementary Table S2, we identified at least 140 DEX incidents spanning 18 distinct attack vectors between 2009 and 2024. Representative vectors include smart contract/protocol exploits (e.g., re-entrancy, logic bugs, oracle/manipulation errors), social engineering attacks, price-manipulation schemes (Blockchain, 2022), rug pulls, website/UI vulnerabilities, private-key compromise (admin/treasury/multisig), cross-chain and bridge weaknesses, double-spend attempts, malicious governance proposals, and flash-loan-enabled exploits.

As shown in Table 6, system exploits (n = 56, 40.0%) and server/private key hacks (n = 39, 27.9%) are by far the most recurrent, together accounting for 95 of the 140 incidents (67.9%). These are followed by flash loan exploits (n = 12, 8.6%), price manipulation attacks (n = 6, 4.3%), and smart contract exploits (n = 7, 5.0%). Collectively, the top five vectors represented 120 of 140 attacks (85.7%). Recent DEX incidents have also produced large aggregate losses relative to many CEX events, thereby reflecting the scale and composability of on-chain protocols (Barbon, 2021). In aggregate, quantified DEX losses totaled $4.303 billion; the top five vectors account for approximately $3.755 billion (87.3%) of the losses (Hong, 2019; Abhishta et al., 2019); see Table 7.

5.1.7.3 Annual losses on CEX and DEX platforms (2009–2024)

Centralized exchanges (CEX) preceded the later arrival of decentralized exchanges (DEX), and their early adoption made CEX the dominant trading model. In 2023, CEX platforms reported an estimated 80 million regular unique users, compared with a peak of 7.5 million unique DEX users in 2021 (Coinweb, 2023; Makridis et al., 2023; Pandya et al., 2019). The broad adoption of both models has attracted persistent criminal activity since 2009 (Collins, 2022; Higbee et al., 2018; Vidal-Tomás, 2021).

CEX yearly losses: Figure 5 illustrates the yearly losses on the CEX platforms grouped by our study’s attack-vector taxonomy. From 2009 to 2022, at least 80 reported incidents resulted in officially reported losses of over $4.191 billion. The largest annual losses occurred in 2018 ($869 million), followed by 2022 ($668.8 million), and 2016 ($628.8 million). From 2014 onward, CEX platforms experienced steady yearly attacks, while incident counts fell during 2019–2022 (13 12 5 4), 2022 still produced a major spike in financial losses Chainalysis (2022), Chainalysis (2023b). The most recurrent CEX vector is the private key/hot wallet/server compromise, accounting for 41 of 80 incidents (51%) and nearly $0.99 billion in aggregate losses (Chainalysis, 2022; Chainalysis 2023b).

DEX yearly losses. Figure 3 shows a breakdown of the total amount lost per year since DEX’s inception of DEX in 2014 owing to different crimes perpetrated against DEX platforms. In aggregate, the quantified losses on DEX totaled $4.303 billion, with 2022 recording the largest annual loss at over $1.918 billion. In recent years, attacks on DEX platforms have increased, reflecting multiple exploitable vulnerabilities in composable on-chain protocols (Badaw et al., 2020).

FIGURE 3

Peak year across platforms. As shown in Figure 6, the single largest combined annual loss occurred in 2022, totaling $2.587 billion across exchanges–$1.918 billion on DEX and $668.8 million on CEX. This peak substantially exceeds adjacent years (e.g., 2021 at $1.823 billion and year-to-date 2024 at $1.018 billion) and coincides with clusters of high-impact DEX exploits and major CEX losses.

Overall total loss. Across 2009–2024, the cumulative losses across exchanges amounted to $8.494 billion ($4.191 B CEX; $4.303 B DEX), consistent with the “Total” bars in Figure 4.

FIGURE 4

5.1.7.4 CEX–DEX incident comparison (and most-attacked platforms)

Figure 3C compares the incident frequencies of the CEX and DEX platforms. The data show that DEX venues experienced more cybersecurity incidents than CEX venues. Although DEXs provide decentralization, permissionless access, and user autonomy, these benefits come with reduced centralized oversight and weaker runtime controls, smart contract vulnerabilities, composability risks, and the absence of centralized monitoring, exposing DEXs to repeated high-impact attacks Chainalysis, 2022; Chainalysis 2023b; Chainalysis Team, 2024).

In contrast, CEXs, despite high-value breaches, tend to operate with stronger operational safeguards (custodial monitoring, layered access control, and compliance/audit programs) that lower the relative frequency of successful incidents (Chohan, 2022). However, both models remain materially exposed and require continuous hardening to ensure their reliability.

Most-attacked platforms. Figure 5 shows venue-level dispersion. In our dataset, the Uniswap DEX platform recorded the highest incidence of attacks, whereas the Binance CEX platform recorded the lowest among the major venues. This aligns with the mechanism-of-risk distinction above: DEX venues inherit smart contracts and composability risk (including human error and governance/upgrade pitfalls), whereas CEX venues benefit from centralized monitoring and coordinated incident responses.

FIGURE 5

5.1.7.5 Repeated and common high-impact attacks on CEX and DEX

As discussed in Section 5.1.5, we define repeated high-impact attacks as vectors that (i) recur more than four times ( distinct occurrences) and (ii) cause losses exceeding $50,000 per incident. Non-property crimes were excluded from this analysis. We enumerated all incidents, tagged recurrent vectors, and tracked both frequency and loss (Tables 7, 8) (McCorry et al., 2018; Holub et al., 2018; Shevchenko et al., 2022). An attack is considered to have a high impact only when it satisfies both criteria.

CEX (repeated high-impact). Using the 10-vector taxonomy (Table 4), four vectors, as shown in Figure 4a exceeded the recurrence threshold and dominated the losses: Unauthorized Wallet Access (39), Server Exploit (10), Insider Exploit (7), and Data Leak/Breach (6). Together, they account for 62 of the 80 incidents (77.5%) and approximately $1.764 billion of $4.191 billion total CEX losses (42.1%). The dominant pattern involves access to hot wallets, which is often enabled by phishing or social engineering techniques (Agarwal et al., 2023).

DEX (repeated high-impact): Of the 18 attack types forming the 140 total DEX incidents (Table 6), five clear the recurrence threshold: System Exploit (56), Server/Private Keys Hacks (39), Flash-Loan Exploit (12), Smart Contract Exploit (7), and Price Manipulation Attack (6). These top five accounted for 120 of 140 incidents (85.7%) and $3.755 billion of $4.303 billion total DEX losses (87.3%) (see Figure 4b; Table 7.)

Combined view. Across both platforms, the repeated high-impact vectors sum to 182 of 220 incidents (82.7%) and $5.519 billion of $8.494 billion combined losses (65.0%), as shown in Figure 4d. This persistence indicates the structural weaknesses that adversaries repeatedly exploit.

Most common attack vectors(CEX vs. DEX): Figures 3d, 6b From our findings, attackers commonly use five attack vectors including API exploits, insider threats, phishing, smart-contract exploits, and unauthorized wallet breaches across CEX and DEX. In CEX, repeated high-impact categories frequently manifest as wallet breaches (often delivered through phishing/API misuse) and insider/API problems. On DEX, smart contracts are exploited, and wallet breaches are dominant. These patterns align with the architectural risk surfaces of each platform (custody and server-side signing on CEX; contract logic, oracles, governance, and cross-chain bridges on DEX).

FIGURE 6

5.1.7.6 Most common attack vector across all exchanges

As shown in Figures 6a,b and Table 7), the dominant repeated vector across platforms is a wallet/key compromise (private key, hot wallet, or server access). This occurred 78 times (39 CEX; 39 DEX): 35.5% of all incidents (78/220) and 42.9% of repeated incidents (78/182), with combined losses of $2.394 B (43.4% of repeated-vector losses and 28.2% of the $8.494 B overall). The next most frequently repeated vectors are the system or server exploits of CEX(10) and DEX(56), that is, (66/182 repeated incidents with $1.979 B lost). Together, these two vectors account for 144/182 repeated incidents (79.1%) and $4.333 B of $5.518 B repeated losses (78.5%); that is, approximately 51% of the overall losses($8.494 B) across 220 incidents) as seen in Figure 6a.

The other repeated vectors (in Figure 4c). Beyond the two platform leaders, four additional repeated vectors show the material impact, listed in the same order as the chart: CEX Insider/Trusted (7 incidents; $0.23 B; $32.9 M/incident), CEX Data Leak/Breach (4; $0.28 B; $70 M/incident), DEX Flash loan (9; $0.41 B; $45.6 M/incident), and DEX Private key/hot wallet/server (repeated subset count) (5; $0.55 B; $110 M/incident).

Two patterns stand out: (i) although less frequent than re-entrancy, DEX private-key compromises are the costliest per incident, and (ii) on CEX, data-leak breaches are rarer but unusually severe on a per-event basis.

The appeal of key and wallet compromise remains clear: attackers obtain signing authority via phishing, social engineering, credential theft, or by breaching the server-side signing infrastructure (Bartoletti et al., 2021; Crystal Blockchain, 2024b; Hedge with Crypto, 2024; Crystal Blockchain, 2024a). A high-profile case is the FTX unauthorized transaction incident in 2022 (approximately $600 M) Fu et al. (2022), after which the platform leadership was criminally prosecuted (Minto, 2022). These observations reinforce the need to harden custody architecture and server-side signing (e.g., HSM/MPC) on CEX while prioritizing secure smart contract development, auditing, and runtime monitoring on DEX.

5.1.7.7 Incidence trends over time

Figure 5a shows the incident counts per year (2009–2024) across all exchanges. Incidents started near zero in 2009–2010 and then rose modestly through 2014 (7) and 2018 (9), before a sharp increase in 2020 (28) and a peak in 2021 (66). The activity remained elevated in 2022 (45) and retreated in 2023 (19) and 2024 (9, year-to-date). Overall, the series showed episodic surges followed by partial pullbacks, consistent with cyclical exposure to a small set of recurrent vectors (see §5.1.7.5).

Figure 6d shows incidents by region (2009–2024). Asia and North America accounted for the largest share, with 60 (27.3%) and 59 (26.8%) incidents, respectively, followed by unknown/global 56 (25.5%), Europe 33 (15.0%), Oceania 10 (4.5%), and Africa 2 (0.9%). The concentrations in Asia and North America likely reflect the scale of their crypto ecosystems and attack surfaces (Cambridge Centre for Alternative Finance, 2017b).

5.1.8 Repeated attacks over time

Figure 6c summarizes the recurrent attack patterns from 2009 to 2024 across five representative vectors: API Exploits, Insider Threats, Phishing, Smart Contract Exploits, and Wallet Breaches. Wallet Breaches are the most frequent and peak notably in 2012 and 2023. Smart contract exploits show consistent activity, with a high point in 2020. Phishing peaked between 2012 and 2020 and subsequently declined, whereas Insider Threats remained relatively stable with minor fluctuations. A modest increase was observed in the discovered API Exploits. Overall, these trends indicate that adversaries repeatedly return to a small set of structurally exposed vectors, which is consistent with the high-impact concentrations quantified in §5.1.7.5.

5.1.9 Financial impact of incidents

Figure 4c summarizes the total loss caused by repeated attack vectors (2009–2024). Using a harmonized taxonomy over the merged dataset, cumulative losses (USD billions) are as follows: Smart-contract exploits $2.216 B; Wallet breaches/key-access $2.108 B; Flash loans $0.440 B; Data leaks/breaches $0.276 B; Phishing/social engineering $0.230 B; Insider/trusted $0.225 B; Compromised system/server $0.039 B; and other/unspecified $2.958 B. Thus, smart contract–related failures and key material compromise together explain roughly (51%) of the cross-platform baseline.

Figure 7a shows the annual losses across exchanges. Loss peaks in 2022 at , remain elevated in 2021 () and 2018 (), and are relatively low in 2019 () and 2016 (). Year-to-date 2024 total .

FIGURE 7

Figure 7b details the regional loss distribution (2009–2024): Asia , North America , Unknown/Global , Europe , Africa , and Oceania . Asia registered the largest cumulative losses, whereas Oceania had minimal cumulative losses during the period.

6 Analysis of attacks techniques and patterns

Table 8 presents an in-depth analysis of numerous attack vectors, methodologies, evolutions, classical defence mechanisms, and widely used quantum defence mechanisms.

As the ecosystem surrounding cryptocurrencies grows in size and development, criminals seeking to identify vulnerabilities in these systems have a level of sophistication (Magizov et al., 2019). The tactics applied by these attackers have grown dynamically, from hacks, phishing, and social engineering to breaches. Quantum computing, which is slowly becoming more prevalent, will open up additional issues, particularly in cryptographic systems tasked with ensuring CExP security. To protect against both classical and quantum attacks, it is important to integrate quantum-safe cryptographic algorithms (Mosca et al., 2024), AI-based anomaly detection, and strong security authentication measures, such as multi-factor authentication and cold storage solutions (Badaw et al., 2020). By following these procedures, cryptocurrency exchanges can strengthen their defenses and mitigate the risks of current and future cyberattacks.

6.1 Impact of cybersecurity attacks on users, exchanges, and the industry

Cyberattacks on cryptocurrency exchanges have serious consequences for users, exchanges, and the broader ecosystem (Navarro, 2019; Alfieri, 2022). Their impacts include:

6.1.1 Impact on users

6.1.2 Impact on exchanges

6.1.3 Impact on the ecosystem

6.1.4 Broader economic impacts

Having quantified the prevalent attack vectors, we next examine the security of the cryptographic primitives underpinning exchanges, both classical and quantum-resilient.

7 Classical cryptographic vulnerabilities and their defense in cryptocurrency exchanges

Classical cryptography defines conventional methods for data and communication security, in which established cryptographic algorithms are applied. Many of these methods are widely applied in the modern digital world to protect information, although they are vulnerable to the growing power of quantum computing (Szymanski, 2022). The following is an overview of classical cryptographic methods. The following is an overview of classical cryptography methods.

7.1 Classical cryptographic mechanisms

Traditional cryptographic measures in cryptocurrency exchanges include public-key encryption, hashing algorithms, multi-signature wallets, and digital signatures (Supplementary Table S5). All these security measures help protect users’ cash, ensure the integrity of transactions, and create a safe channel of communication between exchanges and users (Subramani et al., 2023). They also encounter different challenges, such as the requirement for careful key management to avoid losses and vulnerabilities from cryptographic attacks. In any case, both of the above solutions will certainly play a substantial role in further development and help maintain consistency and security of exchanges in the cryptocurrency ecosystem (Banoth and Regar, 2023).

7.2 Various defense measures on exchanges

Cryptographic systems are fundamental to ensuring the security of cryptocurrency exchange systems. However, attackers can exploit several weaknesses and vulnerabilities. Table 6 summarizes the key vulnerabilities and defense strategies.

8 Post-quantum cryptography and cryptocurrency exchanges

8.1 From classical defenses to quantum threats

Cryptocurrency exchanges currently rely on classical cryptographic mechanisms and layered defence strategies to secure their platforms and protect users from cyberattacks (Weichbroth et al., 2023). These include public key encryption, hashing algorithms, multi-signature wallets, and digital signatures that underpin authentication, transaction integrity, and custodial security. Although these defenses remain effective against current adversaries, they are increasingly strained by the growing sophistication of attacks.

Simultaneously, advances in quantum computing have led to a paradigm shift in cryptographic security. By applying the principles of quantum physics, quantum computers can perform computations beyond the capacity of classical machines (Gill et al., 2022; Rosch-Grace and Straub, 2021). Unlike binary bits, quantum bits (qubits) exist in superposition and enable massive parallelism, thereby allowing quantum systems to solve certain problems exponentially faster than classical systems (Gyongyosi and Imre, 2019; Preskill, 2018). This creates both opportunities and threats: algorithms such as Shor’s and Grover’s jeopardize the hardness assumptions underlying RSA and ECC, exposing exchange infrastructure to harvest-now and decrypt-later risks. Consequently, post-quantum cryptography (PQC) has emerged as a critical frontier for improving exchange resilience.

8.2 Post-quantum cryptography

Post-quantum Cryptography(PQC) denotes cryptographic algorithms designed to withstand the computational power of quantum computers (Fernández-Caramés, 2020; Chen, 2024). Quantum computing poses a potential threat to classic systems, including RSA, ECC, and DH, because their security depends on mathematical problems that any quantum computer can efficiently solve using methods such as Shor’s algorithm. Given the recent advances in quantum computing, the security of conventional cryptography public-key systems has become increasingly insecure. Therefore, quantum-resistant cryptography protocols are urgently required (Mosca et al., 2024; Yi, 2022; National Institute of Standards and Technology, 2024).

The urgency of PQC arises not only from theoretical concerns but also from real-world practices such as “harvest now, decrypt later” attacks, where adversaries store encrypted blockchain traffic today with the intent to decrypt it in the quantum future (Marchsreiter and Sepúlveda, 2023). In response, the NIST PQC standardization project selected lattice-based Kyber (ML-KEM) and Dilithium (ML-DSA) as primary standards (Chen, 2024; Cherkaoui et al., 2024; National Institute of Standards and Technology, 2024), while also advancing Falcon and SPHINCS + for specific use cases (Chen, 2024). This marks a critical turning point in the integration of post-quantum algorithms into the cryptocurrency ecosystem. Crypto-agility, the ability to swiftly migrate to stronger schemes, is now viewed as essential for blockchain protocols (Marchsreiter and Sepúlveda, 2023).

8.3 Types of post-quantum cryptographic algorithms

Currently, research is being conducted to make hybrid systems more efficient in terms of performance, scalability, and efficiency to ensure resistance against emerging threats while providing a smooth transition towards a totally post-quantum-secure setting.

8.4 Impact of quantum computing on classical cryptography

Most cryptocurrency exchange transactions rely on RSA and ECC (Rezaeighaleh and Zou, 2020; Islam et al., 2018); however, quantum computing poses a significant threat to these systems. Shor’s algorithm (Faruk et al., 2022; Kapoor and Thakur, 2022) can efficiently solve the difficult problems underlying these schemes, which modern classical computers cannot (Hussain, 2023; Sharma et al., 2022).

RSA’s security of RSA is based on the difficulty of factoring large numbers (Gangele, 2024); however, Shor’s algorithm can break it in polynomial time, rendering RSA insecure for future quantum adversaries (Vasavi and Latha, 2019; Moussa, 2020). Similarly, ECC, built on the hardness of the discrete logarithm problem, is equally vulnerable to Shor’s algorithm, thereby significantly compromising its security (Olaiya et al., 2024; Padhiar and Mori, 2022). Thus, widely deployed cryptography is obsolete in the quantum era, underscoring the urgency of quantum-resistant alternatives.

8.5 Emerging quantum threats

8.6 Challenges in the post-quantum ERA

Backward compatibility further complicates adoption. Many exchanges rely on ECC for wallets and smart contracts (Ghinea et al., 2023). Migration often requires hybrid approaches (e.g., ECC with Kyber or Dilithium), which increase the payload size and computation, stressing mobile and IoT devices (Ghinea et al., 2023; Cherkaoui et al., 2024; National Institute of Standards and Technology, 2024; Marchsreiter and Sepúlveda, 2023).

8.7 Post-quantum cryptography for cryptocurrency exchanges

8.8 Threat timeline and policy implications

Although the exact timeline for scalable quantum computers remains uncertain, experts have estimated practical threats within 10–15 years (Chen, 2024). Harvest-now and decrypt-later risks require immediate preparation (Marchsreiter and Sepúlveda, 2023). Regulators such as NIST, ETSI, and NSA encourage proactive PQC migration (Chen, 2024; National Institute of Standards and Technology, 2024). Exchanges must implement crypto-agility and begin testing NIST-approved schemes to mitigate systemic risks (Marchsreiter and Sepúlveda, 2023).

9 Discussion

9.1 Research gaps

This review highlights that despite substantial progress in cryptography and blockchain research, important gaps remain in securing cryptocurrency exchanges against classical and quantum adversaries. By curating the first PRISMA-ScR-guided dataset of 220 exchange-only breaches drawn from academic studies, industry reports, and technical disclosures, this study provides a structured evidence base that was absent in previous studies. Our synthesis demonstrates that vulnerabilities are not isolated events but recur systematically; however, existing scholarship has not sufficiently addressed this. These observations build directly on the dataset of 220 validated exchange-only incidents summarized in Section 5, which revealed that vulnerabilities frequently recurred across platforms and years, confirming the systemic nature of the risks discussed here.

First, relatively few studies have examined how the authentication infrastructure of exchanges is exposed to both classical and quantum threats (Chainalysis, 2022; Chainalysis 2023b; IMARC Group, 2023; Oosthoek, 2021; Faruk et al., 2022; Vasavi and Latha, 2019; Olaiya et al., 2024; Sarkis-Onofre et al., 2021). Second, quantum-safe cryptographic algorithms are rarely tailored to the operational realities of exchanges, where latency, throughput, and interoperability are critical (Faruk et al., 2022; Fernández-Caramés, 2020; Easa et al., 2023). Third, multimodal or hybrid post-quantum authentication frameworks are virtually absent in the literature, even though exchanges remain high-value targets (Olaiya et al., 2024; Chen, 2024; Saha et al., 2023; Dharminder et al., 2023; Yi, 2022). Beyond algorithms, practical deployment is rarely simulated in live or large-scale exchange environments (Bucko et al., 2015; De Saint Guilhem et al., 2020; Zhang et al., 2024; Chen, 2024; Saha et al., 2023; Yi, 2022; Panthi and Bhuyan, 2023; Mamatha et al., 2024). Moreover, economic assessments of migration remain underdeveloped, and few studies have quantified the cost-benefit trade-offs of PQC adoption across heterogeneous blockchain ecosystems (Saha et al., 2023; Yi, 2022). Scalability also persists as a problem, with most post-quantum crypto systems untested under high-throughput real-world conditions (Rezaeighaleh and Zou, 2020; Prabakaran and Ramachandran, 2022; Nagarajan et al., 2024; Cherkaoui et al., 2024). Finally, the integration pathways for legacy systems are not clearly articulated, leaving exchange operators without transition roadmaps (John et al., 2023; Dey et al., 2022; Giron et al., 2023). Together, these gaps indicate that both technical design and sociotechnical adoption strategies require further research attention.

9.2 Repeated and dominant attack vectors

Hot wallet compromises are disproportionately prevalent because of the inherent trade-off between accessibility and security issues. Exchanges must maintain hot wallets online to ensure continuous liquidity and rapid settlement; however, this design exposes the private keys to adversaries. Even with safeguards such as multi-signature schemes or withdrawal limits, the online nature of hot wallets increases their susceptibility to theft (Crystal Blockchain, 2024b); Erinle et al., 2023; Sigurdsson et al., 2020). As a result, attackers repeatedly exploit these systemic vulnerabilities, making hot wallet breaches a dominant incident vector. This interpretation aligns with the results showing that wallet and key-management breaches accounted for 78 of the 220 incidents (35%) and approximately $2.39 billion in cumulative losses, confirming their disproportionate impact.

For decentralized exchanges (DEXs), the higher frequency of incidents (140 for DEX vs. 80 for CEXs) yet comparable aggregate losses can be explained by the concentration of attacks on protocols with significant Total Value Locked (TVL). When numerous small-scale exploits occur, adversaries disproportionately target high-value liquidity pools and automated market makers. A single breach in a system protocol with billions of TVL can generate losses equivalent to those in custodial CEX incidents (DefiLlama, 2025a; Chainalysis, 2023b; Nabilou, 2020). This reflects a systemic difference: CEX incidents are commonly tied to custodial infrastructure and authentication, whereas DEX breaches stem from protocol-level weaknesses in smart contracts and governance. As detailed in Table 7; Figure 4, DEX platforms accounted for 140 total incidents, of which 120 (85.7%) were repeated high-impact attacks. Despite the decentralized architecture, these attacks concentrated on high-TVL (Total Value Locked) protocols platforms holding large volumes of user funds, resulting in aggregate losses comparable to centralized exchanges.

9.3 Security of exchanges in the quantum era

Approximately 12% of the incidents in the dataset involved cryptographic or key-management weaknesses, providing the empirical foundation for assessing how quantum algorithms could amplify these vulnerabilities. Our analysis of the incident vectors underscores the need for exchanges to prioritize quantum resilience. Wallet and private key compromises and DEX protocol exploitation dominate historical breaches. In the quantum era, these vectors have become even more dangerous: Shor’s algorithm threatens RSA and ECC, whereas Grover’s algorithm reduces the effective strength of symmetric primitives. As Mosca (2018) warned, the timeline for “Q-day” may be shorter than expected, requiring proactive migration rather than reactive defence.

Our findings have led to the emergence of practical strategies. Continuous monitoring of quantum algorithmic progress must be institutionalized by the exchange operators. Gradual migration to lattice-based encryption (e.g., Kyber) and hash-based signatures (e.g., XMSS and SPHINCS+) should occur through hybrid deployments that preserve backward compatibility with existing RSA/ECC infrastructure. Exchanges must also upgrade Hardware Security Modules (HSMs), authentication servers, and wallet architectures to support PQC natively. Regular quantum-aware risk assessments coupled with third-party audits are essential for validating compliance with emerging standards. Importantly, quantum security cannot be achieved in isolation; collaboration with cybersecurity firms and standardization bodies, such as the NIST, will be vital to ensure interoperability and coordinated adoption.

In this study, post-quantum readiness was assessed using a structured set of indicators derived from both technical and organizational dimensions. At the technical level, we analyzed the proportion of incidents linked to cryptographic or key-management weaknesses (12% of the dataset) (Suga et al., 2020; Oosthoek et al., 2020; Monrat et al., 2019) and evaluated the extent to which exchanges had adopted or tested quantum-safe primitives such as lattice-, hash-, and isogeny-based schemes (Leroux, 2022b; Reijnders, 2023; Ricci et al., 2024; Giron et al., 2023; Singamaneni and Muhammad, 2024). At the organizational level, readiness was gauged through the presence of formal migration planning, use of hardware security modules (HSMs) with PQC compatibility, and evidence of alignment with emerging frameworks such as the NIST PQC standardization roadmap and ETSI QSC guidelines (National Institute of Standards and Technology, 2024; Nosouhi et al., 2024; Mosca, 2018). These indicators collectively formed the basis for evaluating institutional preparedness and quantum-era migration maturity within the exchange ecosystem.

9.4 Implications for operators and regulators

For exchange operators, the dataset shows that 67.9% of recorded incidents stem from two repeated vectors: key compromise and system exploitation. This concentration of risk reflects underlying structural weaknesses in exchange architecture–particularly hot wallet custodianship, key management, and protocol-level controls–that continue to enable repeated exploitation. This finding corresponds to the quantitative pattern in which two repeated vectors–wallet/key compromise and protocol exploitation–jointly accounted for 65% of total recorded losses, highlighting where mitigation should concentrate. Therefore, operators must adopt hybrid PQC schemes in the near term while preparing to transition fully once the standards stabilize. Investments in training, simulation of quantum attacks, and joint R&D with academic partners will accelerate preparedness.

These longitudinal findings, drawn from the 2009–2024 dataset, emphasize that regulatory interventions must address historically recurrent weaknesses rather than isolated breaches. For regulators, this dataset offers a rare longitudinal map of systemic vulnerability. This evidence highlights the urgency of regulatory harmonization, echoing trends seen in frameworks such as the EU Markets in Crypto-Assets (MiCA) regulation and MAS oversight in Singapore. Regulators should define explicit PQC adoption timelines, mandate quantum security audits, and develop incident response protocols that are adapted for quantum-enabled breaches. Without coordinated oversight, fragmented PQC adoption risks leaving exchanges, and, by extension, retail investors are exposed to asymmetric quantum advantages, which highlights the urgency of harmonized oversight, as emphasized in efforts to build standards from past exchange failures (Suga et al., 2020; Johnson, 2020).

9.5 Recommendations for exchange security

The following recommendations derive from empirical patterns identified in Section 5, particularly the dominance of wallet/key and protocol-exploitation vectors responsible for most repeated incidents and financial losses. Several best practices flow directly from this analysis. First, operators must prioritize quantum-resistant cryptography (lattice-based, isogeny-based, and hash-based schemes) for transaction signing and custodianship. Second, mandatory multi-factor authentication must extend beyond SMS or app tokens to include biometric and hardware devices. Third, penetration testing and security audits must explicitly evaluate the implementation of PQC under realistic workloads. Fourth, APIs should be secured through strong authentication, rate limiting, and encryption to reduce the attack surface. Fifth, robust key management practices, including key rotation, segmentation, and HSM-backed cold storage, must be enforced. Finally, layered defense strategies, user education campaigns, and continuous engagement with regulators provide the depth required to withstand both classical and quantum threats.

9.6 Overall significance of the review

This systematic review contributes to the advancement of exchange security scholarship on three levels. Theoretically, it extends cyber-risk and cryptographic migration literature by linking recurrent attack vectors to the technological horizon of quantum computing. Managerially, it provides a longitudinal evidence base that exchange operators can use to prioritize investment in post-quantum architectures, authentication frameworks, and incident-response design. For policy and regulation, it offers empirical benchmarks to inform harmonized oversight, PQC adoption timelines, and audit standards. Collectively, these insights strengthen both scholarly understanding and institutional decision-making for building resilient, quantum-secure digital-asset ecosystems. Together, these contributions position this review as a foundational empirical reference for guiding the secure and quantum-ready evolution of global cryptocurrency exchange infrastructure.

9.7 Limitations

This study has several limitations that should be acknowledged. First, the dataset relies on publicly reported breaches, which may omit incidents suppressed for legal, regulatory, or reputational reasons, introducing a degree of under-reporting bias. Second, the analysis focuses specifically on CEX and DEX platforms, excluding broader DeFi protocols and Layer-2 scaling systems that may exhibit distinct vulnerability patterns and data incompleteness. Third, the evaluation of post-quantum readiness remains forward-looking, as PQC schemes have yet to be widely deployed and tested in live exchange environments. Despite these constraints, the systematic scope of this review provides a robust empirical foundation for future research and policy development.

9.8 Future research directions

Future studies should address these gaps in several ways. Technical research should benchmark PQC schemes under high-throughput exchange workloads to provide empirical evidence of latency and cost effects. Research on crypto-agility,the ability to rapidly switch between cryptographic algorithms, is crucial for managing transitions as PQC standards evolve. Sociotechnical studies are needed to evaluate the user acceptance of PQC-enabled multi-factor authentication, particularly for retail investors. Finally, comparative policy studies should analyze how different jurisdictions mandate PQC migration with a view towards harmonization. Addressing these questions will accelerate scholarly understanding and practical readiness for quantum-secure financial ecosystems.

10 Conclusion

10.1 Summary of findings

10.2 Significance of the study

This review highlights the urgency of transitioning to quantum-resilient cryptographic frameworks to mitigate future threats. As quantum computing matures, the risk of cryptographic failure in virtual asset exchanges increases, thereby threatening the integrity of digital transactions and user trust.

Unlike previous reviews that included wallets or generalized DeFi exploits, this is the first systematic PRISMA-ScR scoping review to assemble and quantitatively analyze the largest unified dataset of CEX and DEX incidents. The novelty lies not only in its exchange-only lens but also in the unprecedented comparability of systemic risks across custodial and non-custodial architectures. By linking 15 years of empirical breach data to emerging quantum risks, this study bridges the gap between retrospective incident analyses and forward-looking post-quantum readiness.

10.3 Call for action

The forward path requires sustained collaboration among regulators, exchange operators, cybersecurity experts, and cryptographers. Through joint efforts, the digital asset ecosystem can be fortified against emerging threats, enabling secure and trustworthy financial innovations in the quantum era.

References

• 1

  AbhishtaA.JoostenR.NieuwenhuisL. J. M. (2019). “Impact of successful ddos attacks on a major crypto-currency exchange,” in 2019 international conference on information and communication technology convergence (ICTC) (Jeju, Korea (South): IEEE), 973–978. 10.1109/ICTC46691.2019.8939862

  • CrossRef
  • Google Scholar

• 2

  AdamikF.KostaS. (2019). “Smartexchange: decentralised trustless cryptocurrency exchange,” in Business information systems workshops (BIS 2018), revised papers (Springer International Publishing), 356–367. 10.1007/978-3-030-04849-5_31

  • CrossRef
  • Google Scholar

• 3

  AgarwalU.RishiwalV.TanwarS.YadavM. (2023). Blockchain and crypto forensics: investigating crypto frauds. Int. J. Netw. Manag.34, e2255. 10.1002/nem.2255

  • CrossRef
  • Google Scholar

• 4

  AhujaP. (2023). Cryptocurrency: a new millennium currency (problem and prospects in India). Int. J. Res. Appl. Sci. and Eng. Technol. (IJRASET)11, 1514–1518. 10.22214/ijraset.2023.54567

  • CrossRef
  • Google Scholar

• 5

  Al-AmriR.ZakariaN. H.HabbalA.HassanS. (2019). Cryptocurrency adoption: current stage, opportunities, and open challenges. Int. J. Adv. Comput. Res.9, 293–307. Identifies current adoption barriers and research gaps. 10.19101/IJACR.PID43

  • CrossRef
  • Google Scholar

• 6

  AL-MubayedhD.AL-KhalisM.AL-AzmanG.AL-AbdaliM.Al FosailM.NagyN. (2019). “Quantum cryptography on ibm qx,” in 2019 2nd international conference on computer applications and information security (ICCAIS), 1–6. 10.1109/CAIS.2019.8769567

  • CrossRef
  • Google Scholar

• 7

  AlauthmanM.Al-QeremA.AlkasassbehM.AslamN.AldweeshA. (2024). “Malware threats targeting cryptocurrency: a comparative study,” in 2024 2nd international conference on cyber resilience (ICCR) (IEEE), 1–8.

  • Google Scholar

• 8

  AlfieriC. (2022). Cryptocurrency and national security. Int. J. Criminol.9. 10.18278/ijc.9.1.3

  • CrossRef
  • Google Scholar

• 9

  AlgazyK.SakanK.NyssanbayevaS.LizunovO. (2024). Syrga2: post-quantum hash-based signature scheme. Computation12, 125. 10.3390/computation12060125

  • CrossRef
  • Google Scholar

• 10

  AlghamdiS. M.Kammoun JarrayaS.KatebF. A. (2024). Enhancing security in multimodal biometric fusion: analyzing adversarial attacks. IEEE Access12, 106133–106145. 10.1109/ACCESS.2024.3435527

  • CrossRef
  • Google Scholar

• 11

  AliaM. A. (2014). Cryptography-based authentication methods. Proc. World Congr. Eng. Comput. Sci. (WCECS 2014) San Francisco, U. S. A Int. Assoc. Eng.2, 468–473.

  • Google Scholar

• 12

  AlzaabiF.MehmoodA. (2024). A review of recent advances, challenges, and opportunities in malicious insider threat detection using machine learning methods. IEEE Access12, 30907–30927. 10.1109/access.2024.3369906

  • CrossRef
  • Google Scholar

• 13

  AmirthalingamG.RadhamaniG. (2014). Multimodal biometric cryptosystem for face and ear recognition based on fuzzy vault. Res. J. Appl. Sci. Eng. Technol.7, 4211–4219. 10.19026/rjaset.7.791

  • CrossRef
  • Google Scholar

• 14

  AnitaN. (2019). “Blockchain security attack: a brief survey,” in 2019 10th international conference on computing, communication and networking technologies (ICCCNT) (IEEE) (Piscataway, NJ: Survey of attack vectors–useful for summarizing security vulnerabilities), 1–7. 10.1109/ICCCNT45670.2019.8944599

  • CrossRef
  • Google Scholar

• 15

  AntonyB.RevathyS. (2024). A novel model for sybil attack detection in online social network using optimal three-stream double attention network. J. Supercomput.80, 7433–7482. 10.1007/s11227-023-05677-3

  • CrossRef
  • Google Scholar

• 16

  Arias-OlivaM.Pelegrín-BorondoJ.Matías-ClaveroG. (2019). “Variables influencing cryptocurrency use: a technology acceptance model in Spain,” in Frontiers in psychology examines psychological and behavioral factors influencing adoption. Useful for evaluating user awareness and behavioral risk.

  • Google Scholar

• 17

  ArliD.van EschP.BakpayevM.LaurenceA. (2021). Do consumers really trust cryptocurrencies?Mark. Intell. and Plan.39, 74–90. Addresses the issue of consumer trust in cryptocurrency ecosystems. Useful for regulatory and perception analysis. 10.1108/MIP-01-2020-0036

  • CrossRef
  • Google Scholar

• 18

  ArunachalamM.SubramanianK. (2015). Aes based multimodal biometric authentication using cryptographic level fusion with fingerprint and finger knuckle print. Int. Arab J. Inf. Technol.

  • Google Scholar

• 19

  AsareB. (2024). “Blockchain technology and vulnerability exploits on smart contracts,” in Blockchain technology and vulnerability exploits on smart contracts.

  • Google Scholar

• 20

  AsprisA.FoleyS.SvecJ.WangL. (2021). Decentralized exchanges: the “wild west” of cryptocurrency trading. Int. Rev. Financial Analysis76, 101845. 10.1016/j.irfa.2021.101845

  • CrossRef
  • Google Scholar

• 21

  AstrakhantsevaI.AstrakhantsevR.LosA. (2021). Cryptocurrency fraud schemes analysis. SHS Web Conf.106, 02001. 10.1051/shsconf/202110602001

  • CrossRef
  • Google Scholar

• 22

  AyeniR.AdebiyiA.OkesolaJ.IgbekeleE. (2024). “Phishing attacks and detection techniques: a systematic review,” in 2024 international conference on science, engineering and business for driving sustainable development goals (SEB4SDG) (IEEE), 1–17.

  • Google Scholar

• 23

  BadawE.JourdanG. V. (2020). Cryptocurrencies emerging threats and defensive mechanisms: a systematic literature review. IEEE Access8, 200021–200037. 10.1109/ACCESS.2020.3034816

  • CrossRef
  • Google Scholar

• 24

  BandaraH.HerathY.WeerasundaraT.AlawatugodaJ. (2022). On advances of lattice-based cryptographic schemes and their implementations. Cryptography6, 56. 10.3390/cryptography6040056

  • CrossRef
  • Google Scholar

• 25

  BanothR.RegarR. (2023). “An introduction to classical and modern cryptography,” in Classical and modern cryptography for beginners (Cham: Springer), 1–12. 10.1007/978-3-031-32959-3_1

  • CrossRef
  • Google Scholar

• 26

  BarbonA.KingT. H. D.WangC. W. (2021). On the quality of cryptocurrency markets: centralized versus decentralized. J. Corp. Finance70, 102049. 10.1016/j.jcorpfin.2021.102049

  • CrossRef
  • Google Scholar

• 27

  BartolettiM.LandeS.LoddoA.PompianuL.SerusiS. (2021). “Cryptocurrency scams: analysis and perspectives,” in Empirical analysis of scams–vital for fraud typology and risk quantification. IEEE Access. 10.1109/ACCESS.2021.3123894

  • CrossRef
  • Google Scholar

• 28

  BashirI. (2020). “Mastering blockchain: a deep dive into distributed ledgers, consensus protocols, smart contracts, DApps, cryptocurrencies, ethereum, and more (packt publishing),” in Comprehensive overview including consensus, tokenization, ethereum 2.0, enterprise blockchain, DeFi, scalability, and DApps. 3rd edn.

  • Google Scholar

• 29

  BasilanM. (2024). Bitcoin tops $107,000, inching closer to google, amazon in market cap ranks. Available online at: https://www.ibtimes.com/bitcoin-tops-107000-inching-closer-google-amazon-market-cap-ranks-3755778.IBTimesUS (Accessed 16 August 2025)

  • Google Scholar

• 30

  BehzadiL.JosephJ. (2024). “Blockchain security considerations,” in Leveraging blockchain technology (Boca Raton, FL: CRC Press), 73–92.

  • Google Scholar

• 31

  BentovI.KumaresanR.MillerA.McCorryP. (2019). “Tesseract: real-time cryptocurrency exchange using trusted hardware,” in Proceedings of the 2019 ACM SIGSAC conference on computer and communications security (CCS ’19) (London, UK: Association for Computing Machinery), 1521–1538. 10.1145/3319535.3355511

  • CrossRef
  • Google Scholar

• 32

  BergstromJ. (2024). A looming threat to bitcoin: the risk of a quantum hack. Available online at: https://johnlothiannews.com/a-looming-threat-to-bitcoin-the-risk-of-a-quantum-hack/.JohnLothianNews (Accessed 16 August 2025)

  • Google Scholar

• 33

  BerryH. S. (2022). The evolution of cryptocurrency and cyber attacks. IEEE Xplore, 1–7. 10.1109/icca56443.2022.10039632

  • CrossRef
  • Google Scholar

• 34

  BhaskarN.ChuenD. (2024). “Bitcoin exchanges,” in Handbook of digital currency (Academic Press), 537–551.

  • Google Scholar

• 35

  BhattA.SisodiaK. (2024). “Operational risks in blockchain technology,” in Leveraging blockchain technology (Boca Raton, FL: CRC Press), 41–56.

  • Google Scholar

• 36

  BhusalC. S. (2021). Systematic review on social engineering: hacking by manipulating humans. J. Inf. Secur.12, 104–114. 10.4236/jis.2021.121005

  • CrossRef
  • Google Scholar

• 37

  BirthriyaS.AhlawatP.JainA. (2024). A comprehensive survey of social engineering attacks: taxonomy of attacks, prevention, and mitigation strategies. J. Appl. Secur. Res.20, 244–292. 10.1080/19361610.2024.2372986

  • CrossRef
  • Google Scholar

• 38

  Bit2Me Academy (2016). Historia de los exchanges y el trading de bitcoin. Available online at: https://academy.bit2me.com/en/historia-exchanges-trading-bitcoin/(Accessed August 16, 2025).

  • Google Scholar

• 39

  BlockchainC. (2022). Crypto and defi hacks, fraud and scams report. Available online at: https://crystalblockchain.com/security-breaches-and-fraud-involving-crypto/.

  • Google Scholar

• 40

  BrownR.BendiabG.ShiaelesS.GhitaB. (2020). “A novel multimodal biometric authentication system using machine learning and blockchain,” in Proceedings of the 12th international network conference (INC 2020) (Rhodes, Greece), 19–21. 10.1007/978-3-030-64758-2_3

  • CrossRef
  • Google Scholar

• 41

  BuckoJ.PalováD.VejačkaM. (2015). “Security and trust in cryptocurrencies,” in Proceedings of the central European conference in finance and economics (CEFE 2015) Košice, Slovakia:Technical University of Košice (Full text available via ResearchGate), 14–24.

  • Google Scholar

• 42

  CaliskanK. (2021). Platform works as stack economization: cryptocurrency markets and exchanges in perspective. Tecnoscienza Italian J. Sci. and Technol. Stud.10.6092/issn.1971-8853/11746

  • CrossRef
  • Google Scholar

• 43

  CaliskanK. (2022). The elephant in the dark: a new framework for cryptocurrency taxation and exchange platform regulation in the us. J. Risk Financial Manag.15, 118. 10.3390/jrfm15030118

  • CrossRef
  • Google Scholar

• 44

  Cambridge Centre for Alternative Finance (2017a). Global cryptocurrency benchmarking study. Available online at: https://www.jbs.cam.ac.uk/wp-content/uploads/2020/08/2017-04-20-global-cryptocurrency-benchmarking-study.pdf.Oneoftheearliestcomprehensivebenchmarkingstudies–setsabaseline.

  • Google Scholar

• 45

  Cambridge Centre for Alternative Finance (2017b). Global cryptocurrency benchmarking study. Tech. Rep., Cambridge centre for alternative finance. Cambridge Judge Business School. Asia-Pacific: 36 via Cambridge University.

  • Google Scholar

• 46

  CCData (2025). “2024 annual exchange review: spot trading volumes,” Tech. Rep.London, United Kingdom: VVData.

  • Google Scholar

• 47

  Chainalysis (2022). “The 2022 crypto crime report,” in Industry report detailing types and trends in crypto-related crime. Central to evidencing real-world threat models. Available online at: https://go.chainalysis.com/rs/503-FAP-074/images/Crypto-Crime-Report-2022.pdf.

  • Google Scholar

• 48

  Chainalysis (2023a). 2023 global crypto adoption index. Available online at: https://www.chainalysis.com/blog/2023-global-crypto-adoption-index/.Breaksdownadoptionacrossregions–centralforsociotechnicalanalysis.

  • Google Scholar

• 49

  Chainalysis (2023b). The chainalysis 2023 crypto crime report. Available online at: https://go.chainalysis.com/2023-crypto-Crime-Report.html.Extendsb9withnewercrimetrends–vitalforcontemporarycybercrimelandscape.

  • Google Scholar

• 50

  Chainalysis Team (2024). 2024 crypto crime trends: illicit activity down as scamming and stolen funds fall, but ransomware and darknet markets see growth. Available online at: https://www.chainalysis.com/blog/2024-crypto-crime-report-introduction/(Accessed August 16, 2025).

  • Google Scholar

• 51

  CharoenwongB. (2022). A decade of cryptocurrency “hacks”: 2011–2021. SSRN Prepr.10.2139/ssrn.3944435

  • CrossRef
  • Google Scholar

• 52

  ChenA. C. H. (2024). The security performance analysis of blockchain systems based on post-quantum cryptography: a case study of cryptocurrency exchanges. Inf. and Commun. Secur. J.15, 34–50. 10.48550/arXiv.2404.16837

  • CrossRef
  • Google Scholar

• 53

  ChenchevI.Aleksieva-PetrovaA.PetrovM. (2021). Authentication mechanisms and classification: a literature survey. Intelligent Comput. Proc. 2021 Comput. Conf.285, 1051–1070. 10.1007/978-3-030-80129-8_69

  • CrossRef
  • Google Scholar

• 54

  CherkaouiI.AliO.HorganJ. (2024). “Novel hybrid post-quantum encryption design on embedded devices,” in 2024 IEEE 29th international conference on emerging technologies and factory automation (ETFA) (IEEE), 1–8. 10.1109/ETFA61755.2024.10794230

  • CrossRef
  • Google Scholar

• 55

  ChernieiV.CherniavskyiS.BabaninaV.TykhoO. (2021). Criminal liability for cryptocurrency transactions: global experience. Eur. J. Sustain. Dev.10, 304. 10.14207/ejsd.2021.v10n4p304

  • CrossRef
  • Google Scholar

• 56

  ChohanU. W. (2022). “The problems of cryptocurrency thefts and exchange shutdowns,” in Social science research network (SSRN) discusses exchange shutdowns and thefts–critical for the section on operational risk.

  • Google Scholar

• 57

  ChutipatV.KasemratR.KraiwanitT.PhaksipaengI. (2023). Selection of cryptocurrency exchange platforms in a developing economy. Corp. and Bus. Strategy Rev.4, 344–350. Discusses platform selection in developing markets–relevant to adoption and decision factors. 10.22495/cbsrv4i2siart14

  • CrossRef
  • Google Scholar

• 58

  CoinDesk (2023). Mt. gox pushes repayments by a year. Available online at: https://www.coindesk.com/business/2023/09/21/mt-gox-pushes-repayments-by-a-year/(Accessed August 16, 2025).

  • Google Scholar

• 59

  CoinMarketCap (2023). Binance exchange information. Available online at: https://coinmarketcap.com/exchanges/binance/.ProvidescurrentmetricsforBinance–usefulforexchangeprofiling.

  • Google Scholar

• 60

  CoinMarketCap (2025). Top cryptocurrency spot exchanges. Available online at: https://coinmarketcap.com/rankings/exchanges/ (Accessed August 16, 2025).

  • Google Scholar

• 61

  Coinpedia (2023). “Global crypto adoption report,” in Adoption statistics globally–useful for user trends section. Available online at: https://coinpedia.org/research-report/global-crypto-adoption-report/.

  • Google Scholar

• 62

  Coinweb (2023). How many crypto wallets are there?. Available online at: https://coinweb.com/trends/how-many-crypto-wallets-are-there/ (Accessed August 16, 2025).

  • Google Scholar

• 63

  CollinsJ. (2022). Crypto crime and control: cryptocurrencies as an enabler of organized crime. Available online at: https://globalinitiative.net/wp-content/uploads/2022/06/GITOC-Crypto-crime-and-control-Cryptocurrencies-as-an-enabler-of-organized-crime.pdf.

  • Google Scholar

• 64

  ConnollyL. Y.WallD. S. (2019). The rise of crypto-ransomware in a changing cybercrime landscape: taxonomising countermeasures. Comput. and Secur.87, 101568. Analyzes the evolution of crypto-ransomware and corresponding defensive strategies. Essential for the cybersecurity threats section. 10.1016/j.cose.2019.101568

  • CrossRef
  • Google Scholar

• 65

  ContiM.KumarS.LalC.RujS. (2018). A survey on security and privacy issues of bitcoin. IEEE Commun. Surv. and Tutorials20, 3416–3452. 10.1109/COMST.2018.2842460

  • CrossRef
  • Google Scholar

• 66

  CorbetS.CummingD. J.LuceyB. M.PeatM.VigneS. A. (2019a). The destabilising effects of cryptocurrency cybercriminality. Econ. Lett.178, 108741. 10.1016/j.econlet.2019.108741

  • CrossRef
  • Google Scholar

• 67

  CorbetS.LuceyB.UrquhartA.YarovayaL. (2019b). Cryptocurrencies as a financial asset: a systematic analysis. Int. Rev. Financial Analysis62, 182–199. 10.1016/j.irfa.2018.09.003

  • CrossRef
  • Google Scholar

• 68

  Cryptohopper (2023). What was the first crypto exchange?. Available online at: https://www.cryptohopper.com/blog/what-was-the-first-crypto-exchange-449 (Accessed August 16, 2025).

  • Google Scholar

• 69

  Crystal Blockchain (2024a). The 10 biggest crypto exchange hacks in history. Published by Crystal Blockchain B.V. Available online at: https://crystalblockchain.com/articles/the-10-biggest-crypto-exchange-hacks-in-history/.

  • Google Scholar

• 70

  Crystal Blockchain (2024b). Security breaches and fraud involving crypto. Ongoing registry breaches–useful industry-wide data points. Available online at: https://crystalblockchain.com/security-breaches-and-fraud-involving-crypto/.

  • Google Scholar

• 71

  Crystal Intelligence (2024). Expert analysis: wazirx hack. Available online at: https://crystalintelligence.com/investigations/expert-analysis-wazirx-hack/.

  • Google Scholar

• 72

  CzaplińskiT.NazmutdinovaE. (2019). Using fiat currencies to arbitrage on cryptocurrency exchanges. J. Int. Stud.12, 184–192. 10.14254/2071-8330.2019/12-1/12

  • CrossRef
  • Google Scholar

• 73

  de Saint GuilhemC. D.FischlinM.WarinschiB. (2020). “Authentication in key-exchange: definitions, relations and composition,” in 2020 IEEE 33rd computer security foundations symposium (CSF) (IEEE), 288–303. 10.1109/CSF49147.2020.00028

  • CrossRef
  • Google Scholar

• 74

  DefiLlama (2025a). 2024 DEX spot trading volume report. Tech. Rep.DefiLlama.

  • Google Scholar

• 75

  DefiLlama (2025b). “2024 perpetual futures volume – centralized exchanges,” Tech. Rep.DefiLlama.

  • Google Scholar

• 76

  DefiLlama (2025c). “2024 perpetual futures volume – decentralized exchanges,” Tech. Rep.DefiLlama.

  • Google Scholar

• 77

  DeyJ.DuttaR. (2023). Progress in multivariate cryptography: systematic review, challenges, and research directions. ACM Comput. Surv.55, 1–34. 10.1145/3571071

  • CrossRef
  • Google Scholar

• 78

  DeyK.DebnathS. K.StănicăP.SrivastavaV. (2022). A post-quantum signcryption scheme using isogeny-based cryptography. J. Inf. Secur. Appl.69, 103280. 10.1016/j.jisa.2022.103280

  • CrossRef
  • Google Scholar

• 79

  DharminderD.ReddyC. B.DasA. K.ParkY.JamalS. S. (2023). Post-quantum lattice-based secure reconciliation enabled key agreement protocol for iot. IEEE Internet Things J.10, 2680–2692. 10.1109/JIOT.2022.3213990

  • CrossRef
  • Google Scholar

• 80

  DimpflT.FladM. (2020). Nothing but noise? Price discovery across cryptocurrency exchanges. J. Financial Mark.52, 100565. 10.1016/j.finmar.2020.100565

  • CrossRef
  • Google Scholar

• 81

  DrzazgaB.KrzywieckiL. (2022). Review of chosen isogeny-based cryptographic schemes. Cryptography6, 27. 10.3390/cryptography6020027

  • CrossRef
  • Google Scholar

• 82

  EasaR. J.YahyaA. S.AhmadE. K. (2023). Protection from a quantum computer cyber-attack: survey. Technium5, 1–12. 10.47577/technium.v5i.8293

  • CrossRef
  • Google Scholar

• 83

  EdwardsD. (2024). “Malware defenses,” in Critical security controls for effective cyber defense: a comprehensive guide to CIS 18 controls (Berkeley, CA: Apress), 277–308. 10.1007/978-1-4842-9738-9_14

  • CrossRef
  • Google Scholar

• 84

  EigelshovenF.AdamM. T. P.BenlianA. (2021). “Cryptocurrency market manipulation: a systematic literature review,” in Proceedings of the forty-second international conference on information systems (ICIS 2021) (Austin, TX, USA: Association for Information Systems).

  • Google Scholar

• 85

  ErinleY.KethepalliY.FengY.XuJ. (2023). Sok: Design, vulnerabilities, and defense of cryptocurrency wallets. Available online at: https://arxiv.org/abs/2307.12874.

  • Google Scholar

• 86

  FalowoO.OzerM.LiC.AbdoJ. (2024). Evolving malware and ddos attacks: decadal longitudinal study. IEEE Access. 10.1109/ACCESS.2024.3376682

  • CrossRef
  • Google Scholar

• 87

  FangF.VentreC.BasiosM.KanthanL.Martinez-RegoD.WuF.et al (2022). Cryptocurrency trading: a comprehensive survey. Financ. Innov.8, 13. 10.1186/s40854-021-00321-6

  • CrossRef
  • Google Scholar

• 88

  FarukM. J. H.RahmanM. A.AlharbiF.AlharbiA.SaadM. A. (2022). “A review of quantum cybersecurity: threats, risks and opportunities,” in Proceedings of the 2022 1st international conference on AI in cybersecurity (ICAIC) (IEEE), 1–7. 10.1109/ICAIC53980.2022.9896970

  • CrossRef
  • Google Scholar

• 89

  FathallaE.AzabM. (2024). Beyond classical cryptography: a systematic review of post-quantum hash-based signature schemes, security, and optimizations. IEEE Access12, 175969–175987. 10.1109/access.2024.3485602

  • CrossRef
  • Google Scholar

• 90

  FederA.GandalN.HamrickJ. T.MooreT. (2017). The impact of ddos and other security shocks on bitcoin currency exchanges: evidence from mt. gox. J. Cybersecurity3, 137–144. 10.1093/cybsec/tyx012

  • CrossRef
  • Google Scholar

• 91

  FengY.ZhouJ.LiJ.ZhaoW.ShiJ.ShiR.et al (2022). Skc-ccco: an encryption algorithm for quantum group signature. Quantum Inf. Process.21, 328. 10.1007/s11128-022-03664-w

  • CrossRef
  • Google Scholar

• 92

  Fernández-CaramésT. M. (2020). Towards post quantum blockchain: a review on blockchain cryptography resistant to quantum computing attacks. IEEE Access. 10.1109/ACCESS.2020.2968985

  • CrossRef
  • Google Scholar

• 93

  FuS.WangQ.YuJ.ChenS. (2022). Ftx collapse: a ponzi story. arXiv Prepr.10.48550/arXiv.2212.09436

  • CrossRef
  • Google Scholar

• 94

  Future Market Insights (2023). Crypto trading platforms market. Relevant for market analysis. Available online at: https://www.futuremarketinsights.com/reports/crypto-trading-platforms-market.Givesindustryforecastandgrowthprojections.

  • Google Scholar

• 95

  GangeleS. (2024). Data security system for a bank based on two different asymmetric algorithms cryptography. Int. J. Multidiscip. Res. (IJFMR)6, 11710. 10.36948/ijfmr.2024.v06i01.11710

  • CrossRef
  • Google Scholar

• 96

  GayathriS.ShanmugamK. (2023). Giottus story–a case study of india’s highly rated crypto exchange. J. Inf. Technol. Teach. Cases14, 282–289. 10.1177/20438869231187662

  • CrossRef
  • Google Scholar

• 97

  GhineaD.KaczmarczyckF.PullmanJ.CretinJ.KölblS.MisoczkiR.et al (2023). “Hybrid post-quantum signatures in hardware security keys,” in Applied cryptography and network security (ACNS 2023) (springer nature Switzerland), vol. 13907 of lecture notes in computer science, 480–499. 10.1007/978-3-031-33623-2_23

  • CrossRef
  • Google Scholar

• 98

  GiechaskielI.CremersC.RasmussenK. B. (2016). “On bitcoin security in the presence of broken cryptographic primitives,” Lect. Notes Comput. Sci., 9558. 201–222. 10.1007/978-3-319-45741-3_11

  • CrossRef
  • Google Scholar

• 99

  GillS. S.KumarA.SinghH.SinghM.KaurK.UsmanM.et al (2022). Quantum computing: a taxonomy, systematic review and future directions. Softw. Pract. Exp.52, 66–114. 10.1002/spe.3039

  • CrossRef
  • Google Scholar

• 100

  GironA. A.CustódioR.Rodríguez-HenríquezF. (2023). Post-quantum hybrid key exchange: a systematic mapping study. J. Cryptogr. Eng.13, 71–88. 10.1007/s13389-022-00288-9

  • CrossRef
  • Google Scholar

• 101

  GohZ. H.WangY.LengL.LiangS.-N.JinZ.LaiY.-L.et al (2022). A framework for multimodal biometric authentication systems with template protection. IEEE Access10, 96388–96402. 10.1109/ACCESS.2022.3205413

  • CrossRef
  • Google Scholar

• 102

  GongG. (2024). Uni/multi variate polynomial embeddings for zksnarks. Cryptogr. Commun.16, 1257–1288. 10.1007/s12095-024-00723-0

  • CrossRef
  • Google Scholar

• 103

  GorkhaliA.LiL.ShresthaA. (2020). Blockchain: a literature review. J. Manag. Anal.7, 321–343. 10.1080/23270012.2020.1801529

  • CrossRef
  • Google Scholar

• 104

  GottipatiH. (2020). A proposed cybersecurity model for cryptocurrency exchanges. Master’s thesis. Edmonton: Concordia University of.

  • Google Scholar

• 105

  GueronS.PersichettiE.SantiniP. (2022). Designing a practical code-based signature scheme from zero-knowledge proofs with trusted setup. Cryptography6, 5. 10.3390/cryptography6010005

  • CrossRef
  • Google Scholar

• 106

  GuptaA.PandaM.GuptaA. (2024a). Advancing Api security: a comprehensive evaluation of authentication mechanisms and their implications for cybersecurity. Int. J. Glob. Innovations Solutions (IJGIS). 10.21428/e90189c8.406d2328

  • CrossRef
  • Google Scholar

• 107

  GuptaS.PritwaniM.ShrivastavaA.MoharirM.ArA. (2024b). “A comprehensive analysis of social engineering attacks: from phishing to prevention-tools, techniques and strategies,” in 2024 second international conference on intelligent cyber physical systems and internet of things (ICoICI) (IEEE), 1–8.

  • Google Scholar

• 108

  GyongyosiL.ImreS. (2019). A survey on quantum computing technology. Comput. Sci. Rev.31, 51–71. 10.1016/j.cosrev.2018.11.002

  • CrossRef
  • Google Scholar

• 109

  HamrickJ. T.ZhangY.XuM.ZhangL.YangY.YanS. (2021). A survey on concept factorization: from shallow to deep representation learning. Inf. Process. and Manag.58, 102534. 10.1016/j.ipm.2021.102534

  • CrossRef
  • Google Scholar

• 110

  HasanM.RozonyF. Z.KamruzzamanM.UddinM. K. S. (2024). Common cybersecurity vulnerabilities: software bugs, weak passwords, misconfigurations, social engineering. Glob. Mainstream J. Innovation, Eng. and Emerg. Technol.3, 42–57. 10.62304/jieet.v3i04.193

  • CrossRef
  • Google Scholar

• 111

  Hedge with Crypto (2024). Cryptocurrency exchange hacks. Available online at: https://www.hedgewithcrypto.com/cryptocurrency-exchange-hacks/.Listshistoricalexchangehacks–practicalcasereferences.

  • Google Scholar

• 112

  HendrixC.LewisR. (2021). Survey on blockchain privacy challenges. USA: University of Colorado, Colorado Springs CO.

  • Google Scholar

• 113

  HigbeeA. (2018). “The role of crypto-currency in cybercrime,” in Computer fraud & security 2018, 5–8. 10.1016/S1361-3723(18)30086-0

  • CrossRef
  • Google Scholar

• 114

  HolubA.ShachtmanA.KaczmarekK.NaikN.ChristinN. (2018). “Coinhoarder: tracking a Ukrainian bitcoin phishing ring dns style,” in 2018 APWG symposium on electronic crime research (eCrime) (IEEE), 1–10. 10.1109/ECRIME.2018.8376208

  • CrossRef
  • Google Scholar

• 115

  HomoliakI.PerešíniM. (2024). Sok: cryptocurrency wallets – a security review and classification based on authentication factors. 1–8. 10.1109/icbc59979.2024.10634439

  • CrossRef
  • Google Scholar

• 116

  HongS. (2019). Survey on analysis and countermeasure for hacking attacks to cryptocurrency exchange. J. Korea Convergence Soc.10, 1–6. 10.15207/JKCS.2019.10.10.001

  • CrossRef
  • Google Scholar

• 117

  HorchA.SittigD.PoseggaJ. (2022). “Adversary tactics and techniques specific to cryptocurrency scams,” in Proceedings of Open Identity Summit 2022 (OID 2022) (Gesellschaft für Informatik), 111–122. 10.18420/OID2022-10

  • CrossRef
  • Google Scholar

• 118

  HorlemannA. L. (2023). “An introduction to code-based cryptography,” in Proceedings of the summer school on finite geometry and friends, 35. Lecture notes/summer school contribution.

  • Google Scholar

• 119

  HussainH. S. (2023). “Cryptocurrency methodologies and techniques,” in The data-driven blockchain ecosystem: fundamentals, applications, and emerging technologies. Editors KhangA.ChowdhuryS.SharmaS. (Boca Raton, FL: CRC Press), CRC Press Information Science and Statistics), 21–29. 10.1201/9781003269281-2

  • CrossRef
  • Google Scholar

• 120

  IkematsuY.NakamuraS.TakagiT. (2023). Recent progress in the security evaluation of multivariate public-key cryptography. IET Inf. Secur.17, 210–226. 10.1049/ise2.12092

  • CrossRef
  • Google Scholar

• 121

  IlliaA.Lawson-BodyA.LeeS.AkalinG. I. (2023). Determinants of cryptocurrency exchange adoption: a conceptual model. Int. J. Technol. Hum. Interact.19, 1–14. 10.4018/IJTHI.326760

  • CrossRef
  • Google Scholar

• 122

  IMARC Group (2023). Cryptocurrency market forecast. Available online at: https://www.imarcgroup.com/cryptocurrency-market.Marketvaluationforecast;strengthenseconomicandadoptionnarrative.

  • Google Scholar

• 123

  InayatU.FarzanM.MahmoodS.ZiaM.HussainS.PallonettoF. (2024). Insider threat mitigation: systematic literature review. Ain Shams Eng. J.103068. 10.1016/j.asej.2023.103068

  • CrossRef
  • Google Scholar

• 124

  IslamM. R.KhanF.Al MahmudA. (2018). “Cryptocurrency vs fiat currency: architecture, algorithm, cashflow and ledger technology on emerging economy,” in 2018 international conference on information and communication technology for the Muslim world (ICT4M) (kuala lumpur, Malaysia: IEEE), 64–69. 10.1109/ICT4M.2018.00020

  • CrossRef
  • Google Scholar

• 125

  JainV.GoyalA.KumarR. (2021). “Coin drop—a decentralised exchange platform,” in Data engineering and communication technology (Springer), 37379–388. Singapore, vol. 73 of Lecture Notes on Data Engineering and Communications Technologies. 10.1007/978-981-16-3961-6_33

  • CrossRef
  • Google Scholar

• 126

  JaniS. (2018). “The growth of cryptocurrency in India: its challenges and potential impacts on legislation,” in ResearchGate analyzes India’s regulatory and societal responses–useful in regional policy comparison.

  • Google Scholar

• 127

  JiaoT.XuZ.QiM.WenS.XiangY.NanG. (2024). A survey of ethereum smart contract security: attacks and detection. Distributed Ledger Technol. Res. Pract.3, 1–28. 10.1145/3643895

  • CrossRef
  • Google Scholar

• 128

  JohnM.OziomaO.NgoziO.EgboghoH. (2023). Lattices in quantum-era cryptography, 3.Int. J. Res. Publ. Rev.10.5281/zenodo.10207209

  • CrossRef
  • Google Scholar

• 129

  JohnsonK. (2020). Decentralized finance: regulating cryptocurrency exchanges. Wm. and Mary Law Rev.62, 1911.

  • Google Scholar

• 130

  KamruzzamanA.ThakurK.AliM. (2024). “Cybersecurity threats using application programming interface (api),” in 2024 international conference on Computing, internet of things and microwave systems (ICCIMS) (IEEE), 1–6.

  • Google Scholar

• 131

  KapoorJ.ThakurD. (2022). “Analysis of symmetric and asymmetric key algorithms,” in ICT analysis and applications (Springer Singapore), 133–143. 10.1007/978-981-16-2377-6_11

  • CrossRef
  • Google Scholar

• 132

  KaseraA. (2020). Cryptocurrency frauds. Int. J. Eng. Adv. Technol. (IJEAT)9, 261–268. 10.35940/ijeat.f1391.089620

  • CrossRef
  • Google Scholar

• 133

  KathedA.YadavA.SinghD. (2019). “An enhanced 3-tier multimodal biometric authentication,” in 2019 international conference on intelligent computing and control systems (ICCS) (Madurai, India: IEEE), 1243–1248. 10.1109/ICCS45141.2019.9065742

  • CrossRef
  • Google Scholar

• 134

  KawaiD.TanakaY.MaehiraT.OriharaR. (2023). User participation in cryptocurrency derivative markets. 5th Conf. Adv. Financial Technol. (AFT 2023) Schloss Dagstuhl – Leibniz-Zentrum für Inf. vol. 282 Leibniz Int. Proc. Inf. (LIPIcs)8, 1–8:20. Explores behavioral trends in crypto derivatives trading. 10.4230/LIPIcs.AFT.2023.8

  • CrossRef
  • Google Scholar

• 135

  KellerA.ScholzM. (2019). “Trading on cryptocurrency markets: analyzing the behavior of bitcoin investors,” in Proceedings of the 40th international conference on information systems (ICIS 2019) (Munich, Germany: Association for Information Systems).

  • Google Scholar

• 136

  KhosraviA.EghlidosT. (2023). Quantum cryptanalysis of symmetric primitives by improving relaxed variants of simon’s algorithm. ISeCure15. 10.22042/ISECURE.2023.198343

  • CrossRef
  • Google Scholar

• 137

  KimC. Y.LeeK. (2018). “Risk management to cryptocurrency exchange and investors guidelines to prevent potential threats,” in 2018 international conference on platform technology and service (PlatCon), 1–6. 10.1109/PlatCon.2018.8472760

  • CrossRef
  • Google Scholar

• 138

  KirazM. (2016). A comprehensive meta-analysis of cryptographic security mechanisms for cloud computing. J. Ambient Intell. Humaniz. Comput.7, 731–760. 10.1007/s12652-016-0385-0

  • CrossRef
  • Google Scholar

• 139

  KrafftP. M.PentlandA.ShmueliE. (2018). “An experimental study of cryptocurrency market dynamics,” in Proceedings of the 2018 ACM conference on economics and computation (EC ’18) (Ithaca, NY, USA: Association for Computing Machinery), 531–548. 10.1145/3219166.3219239

  • CrossRef
  • Google Scholar

• 140

  Ku-MahamudK. R.OmarM.Abu BakarN. A.MurainaI. D. (2019). Awareness, trust, and adoption of blockchain technology and cryptocurrency among blockchain communities in Malaysia. Int. J. Adv. Sci. Eng. Inf. Technol.9, 1217–1222. Regional case study–important for comparative user adoption discussion. 10.18517/ijaseit.9.4.6280

  • CrossRef
  • Google Scholar

• 141

  KuangR.PerepechaenkoM.BarbeauM. (2022). A new post-quantum multivariate polynomial public key encapsulation algorithm. Quantum Inf. Process.21, 360. 10.1007/s11128-022-03712-5

  • CrossRef
  • Google Scholar

• 142

  KumarS.DwivediM.KumarM.GillS. (2024). A comprehensive review of vulnerabilities and ai-enabled defense against ddos attacks for securing cloud services. Comput. Sci. Rev.53, 100661. 10.1016/j.cosrev.2024.100661

  • CrossRef
  • Google Scholar

• 143

  LerouxA. (2022a). “A new isogeny representation and applications to cryptography,” in Advances in cryptology – ASIACRYPT 2022 (springer nature Switzerland), vol. 13793 of lecture notes in computer science, 3–35. 10.1007/978-3-031-22966-4_1

  • CrossRef
  • Google Scholar

• 144

  LerouxA. (2022b). Quaternion algebra and Isogeny-Based cryptography. Paris: Institut Polytechnique de. Ph.D. thesis.

  • Google Scholar

• 145

  LiW.BuJ.LiX.PengH.NiuY.ZhangY. (2022). A survey of defi security: challenges and opportunities. 34, 10378–10404. 10.1016/j.jksuci.2022.10.028

  • CrossRef
  • Google Scholar

• 146

  LimdrianJ.ThorifM.FredyanR.IbrahimM. (2024). “Exploring security in cryptocurrency: challenges, solutions, and implications–a systematic literature review,” in 2024 international conference on ICT for smart Society (ICISS) (IEEE), 1–9. 10.1109/ICISS61969.2024.10699164

  • CrossRef
  • Google Scholar

• 147

  MagizovR.ShaminA.PonomarevE. (2019). “Problems of criminal responsibility for illegal circulation of cryptocurrency,” in 2019 12th international conference on developments in eSystems engineering (DeSE) (IEEE), 633–638. 10.1109/DeSE.2019.00185

  • CrossRef
  • Google Scholar

• 148

  MakridisC. A.FröwisM.SridharK.BöhmeR. (2023). The rise of decentralized cryptocurrency exchanges: evaluating the role of airdrops and governance tokens. J. Corp. Finance79, 102358. 10.1016/j.jcorpfin.2023.102358

  • CrossRef
  • Google Scholar

• 149

  MalviyaA. K.TiwariN.ChawlaM. (2022). Quantum cryptanalytic attacks of symmetric ciphers: a review. Comput. Electr. Eng.101, 108122. 10.1016/j.compeleceng.2022.108122

  • CrossRef
  • Google Scholar

• 150

  MamathaG. S.DimriN.SinhaR. (2024). Post-quantum cryptography: securing digital communication in the quantum era. arXiv Prepr. arXiv:2403. 10.48550/arXiv.2403.11741

  • CrossRef
  • Google Scholar

• 151

  ManimuthuA.SreedharanV. R.RejikumarG.MarwahaD. (2019). “A literature review on bitcoin: transformation of crypto currency into a global phenomenon,” in Relevant for the historical background. IEEE Engineering Management Review Reviews Bitcoin’s emergence and its implications for global economic systems.

  • Google Scholar

• 152

  ManthovaniR. (2023). A comparative analysis of money laundering crimes in Indonesia through cryptocurrency. Int. J. Cyber Criminol.10.5281/zenodo.4766612

  • CrossRef
  • Google Scholar

• 153

  MarchsreiterD.SepúlvedaJ. (2023). “A pqc and qkd hybridization for quantum-secure communications,” in 2023 26th euromicro conference on digital system design (DSD) (IEEE), 545–552. 10.1109/DSD60801.2023.00079

  • CrossRef
  • Google Scholar

• 154

  MarellaV.ZengD.WangH. (2021). “Rebuilding trust in cryptocurrency exchanges after cyber-attacks,” in Proceedings of the 54th Hawaii international conference on system sciences (HICSS 2021) (hawaii, USA: hawaii international conference on system sciences), 6314–6323. Focuses on post-attack strategies for trust restoration. 10.24251/HICSS.2021.758

  • CrossRef
  • Google Scholar

• 155

  MaríaN. P. (2024). “Post-quantum symmetric cryptography,” in Symmetric cryptography, volume 2: cryptanalysis and future directions (Springer), 203. 10.1007/978-3-031-23304-3_9

  • CrossRef
  • Google Scholar

• 156

  MateenM. (2023). Regulation in the cryptocurrency industry. Thesis: University of Missouri-Kansas City.

  • Google Scholar

• 157

  MattosS. M.CestariV. R. F.MoreiraT. M. M. (2023). Scoping protocol review: prisma-scr guide refinement. Rev. Enferm. UFPI12. 10.26694/reufpi.v12i1.3062

  • CrossRef
  • Google Scholar

• 158

  McCorryP.MöserM.AliS. T. (2018). “Why preventing a cryptocurrency exchange heist isn’t good enough,” in Security protocols XXVI (Cham: Springer), 150–158. 11286 of Lecture Notes in Computer Science. 10.1007/978-3-030-03251-7_12

  • CrossRef
  • Google Scholar

• 159

  MintoA. (2022). The legal characterization of crypto-exchange platforms. Glob. Jurist22, 137–156. 10.1515/gj-2020-0085

  • CrossRef
  • Google Scholar

• 160

  MohammadiR.HosseiniM.BahramiR. (2024). “Uncovering security vulnerabilities through multiplatform malware analysis,” in Security and privacy, e455. 10.1002/spy2.455

  • CrossRef
  • Google Scholar

• 161

  MohsinK. (2022). Cryptocurrency legality and regulations – an international scenario. Int. J. Cryptocurrency Res.2, 19–29. 10.51483/IJCCR.2.1.2022.19-29

  • CrossRef
  • Google Scholar

• 162

  MonratA. A.SchelenO.AnderssonK. (2019). A survey of blockchain from the perspectives of applications, challenges, and opportunities. IEEE ACCESS7, 117134–117151. 10.1109/ACCESS.2019.2936094

  • CrossRef
  • Google Scholar

• 163

  MorinA.DandekarV.SmarandacheA. (2023). “How cryptocurrency exchange interruptions create arbitrage opportunities,” in 2023 IEEE European symposium on security and privacy workshops (EuroS&PW) (IEEE), 33–40. 10.1109/EuroSPW59978.2023.00028

  • CrossRef
  • Google Scholar

• 164

  MoscaM. (2018). Cybersecurity in an era with quantum computers: will we be ready?Tech. Rep. Glob. Risk Inst.16, 38–41. 10.1109/msp.2018.3761723

  • CrossRef
  • Google Scholar

• 165

  MoscaM.PianiM. (2024). “Quantum threat timeline report 2024,” Tech. Rep.Toronto, Canada: Global Risk Institute.

  • Google Scholar

• 166

  MoussaW.NadiaB.InesG. (2020). Asymmetric effect and dynamic relationships over the cryptocurrencies market. Comput. and Secur.96, 101860. 10.1016/j.cose.2020.101860

  • CrossRef
  • Google Scholar

• 167

  MunnZ.PetersM. D. J.SternC.TufanaruC.McArthurA.AromatarisE. (2018). Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review. BMC Med. Res. Methodol.18, 1–7. 10.1186/s12874-018-0611-x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 168

  MunnZ.PollockD.KhalilH.AlexanderL.MclnerneyP.GodfreyC. M.et al (2022). What are scoping reviews? Providing a formal definition of scoping reviews as a type of evidence synthesis. JBI Evid. Synth.20, 950–952. 10.11124/JBIES-21-00483

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 169

  MurugappanM.NairR.KrishnanS. (2023). Global market perceptions of cryptocurrency and the use of cryptocurrency by consumers: a pilot study. J. Theor. Appl. Electron. Commer. Res.18, 1955–1970. 10.3390/jtaer18040098

  • CrossRef
  • Google Scholar

• 170

  NabilouH. (2020). The dark side of licensing cryptocurrency exchanges as payment institutions. Law Financial Mark. Rev.14, 39–47. 10.1080/17521440.2019.1626545

  • CrossRef
  • Google Scholar

• 171

  NagarajanG.GopiR. M.SanjaiR. (2024). “Role of hash-based signatures in quantum cryptography,” in AIP conference proceedings (AIP publishing), 3075020007.10.1063/5.0212709

  • CrossRef
  • Google Scholar

• 172

  NakamotoS. (2008). Bitcoin: A peer-to-peer electronic cash system. SSRN 3440802

  • Google Scholar

• 173

  NakamotoS. (2009). Bitcoin: a peer-to-peer electronic cash system. Available online at: https://bitcoin.org/bitcoin.pdf.

  • Google Scholar

• 174

  National Institute of Standards and Technology (2024). Nist releases first 3 finalized post-quantum encryption standards. NIST News. Online

  • Google Scholar

• 175

  NavamaniT. M. (2021). A review on cryptocurrencies security. Journal of Applied Security Research. Oxfordshire, United Kingdom: Taylor & Francis. 10.1080/19361610.2021.1933322

  • CrossRef
  • Google Scholar

• 176

  NavarroR. R. (2019). Preventative fraud measures for cryptocurrency exchanges: mitigating the risk of cryptocurrency scams. Utica Coll. Thesis.

  • Google Scholar

• 177

  NosouhiM. R.SoodK.ChamolaV.JeongJ. J.GaddamA. (2024). Towards quantum-secure software defined networks. IET Quantum Commun.5, 66–71. 10.1049/qtc2.12073

  • CrossRef
  • Google Scholar

• 178

  OlaiyaO. P.AdesogaT. O.AdebayoA. A.SotomiF. M.AdigunO. A.EzelioraP. M. (2024). Encryption techniques for financial data security in fintech applications. Int. J. Sci. Res. Archive12, 2942–2949. 10.30574/ijsra.2024.12.1.1210

  • CrossRef
  • Google Scholar

• 179

  OlaniyanJ.OgunolaA. A. (2024). Protecting small businesses from social engineering attacks in the digital era. World J. Adv. Res. Rev.24, 834–853. 10.30574/wjarr.2024.24.3.3745

  • CrossRef
  • Google Scholar

• 180

  OosthoekK. (2021). “Cyber security threats to bitcoin exchanges: adversary exploitation and laundering techniques,” in Covers cyber-attack strategies and laundering–technical depth for risk section. IEEE Transactions on Network and Service Management. 10.1109/TNSM.2020.3046145

  • CrossRef
  • Google Scholar

• 181

  OosthoekK.BowenB. M.HutchisonD. (2020). “From hodl to heist: analysis of cyber security threats to bitcoin exchanges,” in 2020 IEEE international conference on blockchain and cryptocurrency (ICBC) (IEEE), 1–8. 10.1109/ICBC48266.2020.9169412

  • CrossRef
  • Google Scholar

• 182

  PadhiarS.MoriK. H. (2022). A comparative study on symmetric and asymmetric key encryption techniques. Implement. Data Anal. Archit. Next Generation Wirel. Commun. IGI Glob., 132–144. 10.4018/978-1-7998-6988-7.ch008

  • CrossRef
  • Google Scholar

• 183

  PaganiniP. (2018). Group-ib: 14 cyber attacks on crypto exchanges resulted in a loss of $882 million. Available online at: https://securityaffairs.co/77213/hacking/cyber-attacks-crypto-exchanges.html. Security Affairs(Accessed 16 August 2025)

  • Google Scholar

• 184

  PageM. J.McKenzieJ. E.BossuytP. M.BoutronI.HoffmannT. C.MulrowC. D.et al (2021). The prisma 2020 statement: an updated guideline for reporting systematic reviews. BMJ372, n71. 10.1136/bmj.n71

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 185

  PanD.LongG-LYinL.ShengY-BRuanD.Xin NgS. (2024). The evolution of quantum secure direct communication: on the road to the qinternet. IEEE Commun. Surv. and Tutorials. 10.1109/COMST.2024.3372208

  • CrossRef
  • Google Scholar

• 186

  PandyaS.MittapalliM.GullaS. V. T.LandauO. (2019). Cryptocurrency: adoption efforts and security challenges in different countries. HOLISTICA10, 167–186. 10.2478/hjbpa-2019-0024

  • CrossRef
  • Google Scholar

• 187

  PanjwaniP. (2023). S Korean crypto exchange gdac hacked for nearly $13m. Available online at: https://www.coindesk.com/tech/2023/04/10/s-korean-crypto-exchange-gdac-hacked-for-nearly-13m/.CoinDesk (Accessed 16 August 2025)

  • Google Scholar

• 188

  PanthiS.BhuyanB. (2023). “Quantum-resistant hash-based digital signature schemes: a review,” in Frontiers in computing and systems (Springer Nature Singapore), 637–655. 10.1007/978-981-99-8147-8_46

  • CrossRef
  • Google Scholar

• 189

  PatashkovaY.NiyazbekovaS.KerimkhulleS.SerikovaM.TroyanskayaM. (2021). Dynamics of bitcoin trading on the binance cryptocurrency exchange. Econ. Annals-XXI187, 177–188. 10.21003/ea.V187-17

  • CrossRef
  • Google Scholar

• 190

  PatelS. M. (2022). Fraud on the crypto market. Harv. J. Law Technol.10.2139/ssrn.4278973

  • CrossRef
  • Google Scholar

• 191

  PatelS.SinghH.ChatterjeeP.SaxenaA. (2019). “Dauth: a decentralized web authentication system using ethereum based blockchain,” in 2019 IEEE international conference on blockchain (Blockchain-2019) (IEEE), 208–215. 10.1109/Blockchain.2019.00033

  • CrossRef
  • Google Scholar

• 192

  PooniaL.TinkerS. (2024). A comprehensive analysis of the types, impacts, prevention, and mitigation of ddos attacks. Recent Patents on Engineering

  • Google Scholar

• 193

  PrabakaranD.RamachandranS. (2022). Multi-factor authentication for secured financial transactions in cloud environment. CMC-Computers, Mater. and Continua70, 1781–1798. 10.32604/cmc.2022.019846

  • CrossRef
  • Google Scholar

• 194

  PrendiL.BorakajD.PrendiK. (2023). The new money laundering machine through cryptocurrency: current and future public governance challenges. Corp. Law and Gov. Rev.5, 84–91. 10.22495/clgrv5i2p9

  • CrossRef
  • Google Scholar

• 195

  PreskillJ. (2018). Quantum computing in the nisq era and beyond. Quantum2, 79. 10.22331/q-2018-08-06-79

  • CrossRef
  • Google Scholar

• 196

  PurohitH.DadhichM.AjmeraP. K. (2023). Analytical study on users’ awareness and acceptability towards adoption of multimodal biometrics (mmb) mechanism in online transactions: a two-stage sem-ann approach. Multimedia Tools Appl.82, 14239–14263. 10.1007/s11042-022-13786-z

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 197

  RaniS.S. Vennila Fathima Rani (2024). Securing digital wallets: threats and countermeasures. mLAC J. Arts, Commer. Sci. (m-JACS)2, 25–32. 10.59415/mjacs.v2i4.185

  • CrossRef
  • Google Scholar

• 198

  ReijndersK. (2023). “Effective pairings in isogeny-based cryptography,” in Progress in cryptology – LATINCRYPT 2023 (springer nature Switzerland), vol. 14203 of lecture notes in computer science, 109–128. 10.1007/978-3-031-47637-2_6

  • CrossRef
  • Google Scholar

• 199

  RejebA.RejebK.KeoghJ. G. (2021). Cryptocurrencies in modern finance: a literature review. Etikonomi20, 93–118. Literature review summarizing cryptocurrency’s financial impact. Good overview source. 10.15408/etk.v20i1.16911

  • CrossRef
  • Google Scholar

• 200

  RenL.ZhangD. (2022). A qr code-based user-friendly visual cryptography scheme. Sci. Rep.12, 7667. 10.1038/s41598-022-11871-9

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 201

  ReynoldsM. (2025). Q-day is coming: the apocalypse of encryption. Wired.

  • Google Scholar

• 202

  RezaeighalehH.ZouC. C. (2020). “Multilayered defense-in-depth architecture for cryptocurrency wallet,” in 2020 IEEE 6th international conference on computer and communications (ICCC) (IEEE), 2212–2217. 10.1109/ICCC51575.2020.9345013

  • CrossRef
  • Google Scholar

• 203

  RicciS.DobiasP.MalinaL.HajnyJ.JedlickaP. (2024). Hybrid keys in practice: combining classical, quantum and post-quantum cryptography. IEEE Access12, 23206–23219. 10.1109/access.2024.3364520

  • CrossRef
  • Google Scholar

• 204

  Rosch-GraceD.StraubJ. (2021). “Analysis of the necessity of quantum computing capacity development for national defense and homeland security,” in 2021 IEEE international symposium on technologies for homeland security (HST), 1–8. 10.1109/HST53381.2021.9619831

  • CrossRef
  • Google Scholar

• 205

  RotA.BlaickeB. (2019). “Blockchain’s future role in cybersecurity: analysis of defensive and offensive potential,” in 2019 9th international conference on advanced computer information technologies (ACIT) (IEEE), 447–451. 10.1109/ACITT.2019.8779860

  • CrossRef
  • Google Scholar

• 206

  RoyK. S. (2019). A survey on post-quantum cryptography for constrained devices. International Journal of Applied Engineering Research. (India: Research India Publications)

  • Google Scholar

• 207

  RuizE. P.AngelisJ. (2022). Combating money laundering with machine learning – applicability of supervised-learning algorithms at cryptocurrency exchanges. J. Money Laund. Control25, 766–778. 10.1108/jmlc-09-2021-0106

  • CrossRef
  • Google Scholar

• 208

  RuotiS.KaiserB.YerukhimovichA.ClarkJ.CunninghamR. (2020). Blockchain technology: what is it good for?Commun. ACM63, 46–53. 10.1145/3369752

  • CrossRef
  • Google Scholar

• 209

  SahaR.KumarG.DevgunT.BuchananW. J.ThomasR.AlazabM.et al (2023). A blockchain framework in post-quantum decentralization. IEEE Trans. Serv. Comput.16, 1–12. 10.1109/TSC.2021.3116896

  • CrossRef
  • Google Scholar

• 210

  SanthoshA.SubramanianN. (2024a). “Classify attacks based on blockchain components,” in 2024 12th international symposium on digital forensics and security (ISDFS) (IEEE), 1–6.

  • Google Scholar

• 211

  SanthoshA.SubramanianN. (2024b). “Classify attacks based on blockchain components,” in 2024 12th international symposium on digital forensics and security (ISDFS) (IEEE), 1–6. 10.1109/ISDFS60427.2024.10663992

  • CrossRef
  • Google Scholar

• 212

  Sarkis-OnofreR.Catalá-LópezF.AromatarisE.LockwoodC. (2021). How to properly use the prisma statement. Syst. Rev.10, 117. 10.1186/s13643-021-01671-z

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 213

  ScharfmanJ. (2023). The cryptocurrency and digital asset fraud casebook. Springer Nature Switzerland AG. 10.1007/978-3-031-23679-2

  • CrossRef
  • Google Scholar

• 214

  SenguptaJ.RujS.BitS. D. (2020). A comprehensive survey on attacks, security issues and blockchain solutions for iot and iiot. J. Netw. Comput. Appl.149, 102481. 10.1016/j.jnca.2019.102481

  • CrossRef
  • Google Scholar

• 215

  ShajiN. A.BasheerM.RamyaR. S. (2022). “Geofencing and cryptocurrency exchange platforms with blockchain anonymity,” in 2022 IEEE 7th international conference on recent advances and innovations in engineering (ICRAIE) (IEEE), 1–6. 10.1109/ICRAIE56454.2022.10054294

  • CrossRef
  • Google Scholar

• 216

  ShaliniS.SanthiH. (2019). “A survey on various attacks in bitcoin and cryptocurrency,” in 2019 international conference on communication and signal processing (ICCSP) (IEEE), 0329–0333. 10.1109/ICCSP.2019.8698003

  • CrossRef
  • Google Scholar

• 217

  ShandilyaS.DattaA.KartikY.NagarA. (2024). “A study in attack and breaches,” in Digital resilience: navigating disruption and safeguarding data privacy (Boca Raton, FL: CRC Press), 279–309.

  • Google Scholar

• 218

  SharmaD. K.SinghN. C.NoolaD. A.DossA. N.SivakumarJ. (2022). A review on various cryptographic techniques and algorithms. Mater. Today Proc.51, 104–109. 10.1016/j.matpr.2021.05.483

  • CrossRef
  • Google Scholar

• 219

  ShevchenkoP. V.JangJ.MalavasiM.PetersG. W.SofronovG.TrückS. (2022). The illogic of plausible deniability: why proxy conflict in cyberspace May no longer pay. J. Cybersecurity8, tyac007. 10.1093/cybsec/tyac007

  • CrossRef
  • Google Scholar

• 220

  ShouC.KeY.YangY.SuQ.DadoshO.EliA.et al (2024). Backrunner: mitigating smart contract attacks in the real world. ArXiv preprint arXiv:2409.06213. Available online at: https://arxiv.org/abs/2409.06213.

  • Google Scholar

• 221

  SigalosM. (2023). Sam bankman-fried found guilty on all seven criminal fraud counts. Available online at: https://www.cnbc.com/2023/11/02/sam-bankman-fried-found-guilty-on-all-seven-criminal-fraud-counts.html.CNBC (Accessed 16 August 2025)

  • Google Scholar

• 222

  SigurdssonG.PeturssonA.KristjanssonK. (2020). “Vulnerabilities and security breaches in cryptocurrencies,” in Blockchain and cryptocurrency: legal and security considerations (Springer Nature Switzerland), 87–102. 10.1007/978-3-030-56784-5_6

  • CrossRef
  • Google Scholar

• 223

  SingamaneniK. K.MuhammadG. (2024). A novel integrated quantum-resistant cryptography for secure scientific data exchange in ad hoc networks. Ad Hoc Netw.164, 103607. 10.1016/j.adhoc.2024.103607

  • CrossRef
  • Google Scholar

• 224

  SinghM. K. (2022). “Code-based cryptography: a comparative study of key sizes,” in Advanced communication and intelligent systems (Springer Nature Switzerland), 359–368. 10.1007/978-3-031-21407-3_32

  • CrossRef
  • Google Scholar

• 225

  SoanaG. (2024). The anti-money laundering regulation of crypto-assets in Europe: a critical analysis, 13. of Giustizia penale europea (CEDAM).

  • Google Scholar

• 226

  SobralJ. (2022). On the security of multivariate encryption schemes. J. Inf. Secur.

  • Google Scholar

• 227

  SoskaK.ChristinN.EskandariS. (2021). “Towards understanding cryptocurrency derivatives: a case study of bitmex,” in Proceedings of the 2021 ACM SIGSAC conference on computer and communications security (CCS) (ACM), 1736–1753. 10.1145/3460120.3484592

  • CrossRef
  • Google Scholar

• 228

  SouzaO. T.CarvalhoJ. V. F. (2022). Market efficiency assessment for multiple exchanges of cryptocurrencies. Rev. Gestão (REGE)31, 137–151. 10.1108/REGE-05-2022-0070

  • CrossRef
  • Google Scholar

• 229

  SrivastavaV.BaksiA.DebnathS. K. (2023). An overview of hash-based signatures. Cryptol. ePrint Arch. Rep. 2023/639. Available online at: https://eprint.iacr.org/2023/639.

  • Google Scholar

• 230

  StovoldE.BeecherD.FoxleeR.Noel-StorrA. (2014). Study flow diagrams in cochrane systematic review updates: an adapted prisma flow diagram. Syst. Rev.3, 54. 10.1186/2046-4053-3-54

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 231

  SubramaniS.SelviM.KannanA.Santhosh KumarS. V. N. (2023). “Review of security methods based on classical cryptography and quantum cryptography,” in Cybernetics and systems. 10.1080/01969722.2023.2166261

  • CrossRef
  • Google Scholar

• 232

  SugaY.ShimaokaM.SatoM.NakajimaH. (2020). “Securing cryptocurrency exchange: building up standard from huge failures,” in Financial cryptography and data security: FC 2020 international workshops, AsiaUSEC, CoDeFi, VOTING, and WTSC (Springer International Publishing), 254–270. 10.1007/978-3-030-54455-3_19

  • CrossRef
  • Google Scholar

• 233

  SumalathaU.PrakashaK. K.PrabhuS.NayakV. C. (2024). A comprehensive review of unimodal and multimodal fingerprint biometric authentication systems: fusion, attacks, and template protection. IEEE Access12, 64300–64334. 10.1109/ACCESS.2024.3395417

  • CrossRef
  • Google Scholar

• 234

  SzymanskiT. H. (2022). The cyber security via determinism’ paradigm for a quantum-safe zero trust deterministic internet of things (iot). IEEE Access10, 45893–45930. 10.1109/ACCESS.2022.3169137

  • CrossRef
  • Google Scholar

• 235

  TakahashiH.SatoH.KonoK. (2019). “Multiple layered security analyses method for cryptocurrency exchange servicers,” in 2019 IEEE 8th global conference on consumer electronics (GCCE) (IEEE), 775–779. 10.1109/GCCE46687.2019.9015207

  • CrossRef
  • Google Scholar

• 236

  TandonA.NayyarA. (2019). “A comprehensive survey on ransomware attack: a growing havoc cyberthreat,” in Cybersecurity issues in emerging technologies (Singapore: Springer), 1–27. 10.1007/978-981-13-8775-3_1

  • CrossRef
  • Google Scholar

• 237

  ThanalakshmiP.RishikheshA.Marion MarcelineJ.JoshiG.ChoW. (2023). A quantum-resistant blockchain system: a comparative analysis. Mathematics11, 3947. 10.3390/math11183947

  • CrossRef
  • Google Scholar

• 238

  TomJ. J.P. AneboD. N.OnyekweluD. B. A.WilfredA.E. EyoR. (2023). Quantum computers and algorithms: a threat to classical cryptographic systems. Int. J. Eng. Adv. Technol. (IJEAT)12, 25–38. 10.35940/ijeat.E4153.0612523

  • CrossRef
  • Google Scholar

• 239

  TriccoA. C.LillieE.ZarinW.O’BrienK.ColquhounH.KastnerM.et al (2016). A scoping review on the conduct and reporting of scoping reviews. BMC Med. Res. Methodol.16, 15. 10.1186/s12874-016-0116-4

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 240

  TripathiS.GuptaA.KumarR.AggarwalS. (2023). Tex – true exchange: decentralized cryptocurrency exchange for indian marketsLes Ulis, France: EDP Sciences. 01158, 430. 10.1051/e3sconf/202343001158

  • CrossRef
  • Google Scholar

• 241

  Triple-A Technologies Pte. Ltd (2024). The state of global cryptocurrency ownership in 2024. Available online at: https://www.triple-a.io/cryptocurrency-ownership-data/. Foreword by Eric Barbier(Accessed 16 August 2025)

  • Google Scholar

• 242

  TrozzeA.KampsJ.AkartunaE. A.HetzelF. J.KleinbergB.DaviesT.et al (2022). Cryptocurrencies and future financial crime. Crime Sci.11, 1. 10.1186/s40163-021-00163-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 243

  VasaviK.LathaY. (2019). Rsa cryptography based multi-modal biometric identification system for high-security application. Int. J. Intelligent Eng. Syst.12, 10–21. 10.22266/ijies2019.0228.02

  • CrossRef
  • Google Scholar

• 244

  VasekM.MooreT. (2018). “Analyzing the bitcoin ponzi scheme ecosystem,” Proc. Bitcoin Workshop, Lect. Notes Comput. Sci., 10958. 101–112. 10.1007/978-3-662-58820-8_8

  • CrossRef
  • Google Scholar

• 245

  VasekM.ThorntonM.MooreT. (2014). “Empirical analysis of denial-of-service attacks in the bitcoin ecosystem,” in Financial cryptography and data security (FC 2014), Lect. Notes Comput. Sci.8438. 57–71. 10.1007/978-3-662-44774-1_5

  • CrossRef
  • Google Scholar

• 246

  Vergara-MerinoB.Vargas-PeiranoL.Silva-DreyerA. M.Vergara-MerinoL.Vargas-PeiranoM. (2021). What you need to know about scoping reviews. Medwave21, e8144. 10.5867/medwave.2021.02.8144

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 247

  VeroniM. (2023). A study on tighter and more efficient isogeny-based cryptographic protocols

  • Google Scholar

• 248

  VictorF.WeintraudB. (2021). “Detecting and quantifying wash trading on decentralized cryptocurrency exchanges,” in Proceedings of the web conference 2021 (WWW ’21) (ACM), 23–32. 10.1145/3442381.3449824

  • CrossRef
  • Google Scholar

• 249

  Vidal-TomásD. (2021). An investigation of cryptocurrency data: the market that never sleeps. Quant. Finance21, 2007–2024. 10.1080/14697688.2021.1930124

  • CrossRef
  • Google Scholar

• 250

  Vidal-TomásD. (2022). Which cryptocurrency data sources should scholars use?Int. Rev. Financial Analysis81, 102061. 10.1016/j.irfa.2022.102061

  • CrossRef
  • Google Scholar

• 251

  VitalL. C. (2022). Crypto-crime: the evolution of criminal finances using digital assets. Utica, NY: Utica University Thesis.

  • Google Scholar

• 252

  Wachter-ZehA.BartzH.LivaG. (2022). Code-based cryptography. IEEE Access10, 118876–118911. 10.1109/ACCESS.2022.3218765

  • CrossRef
  • Google Scholar

• 253

  WangX.XuG.YuY. (2023). Lattice-based cryptography: a survey. Chin. Ann. Math. Ser. B44, 945–960. 10.1007/s11401-023-0053-6

  • CrossRef
  • Google Scholar

• 254

  WangY.ShengS.WangY. (2024a). “A systematic literature review on smart contract vulnerability detection by symbolic execution,” in Blockchain and trustworthy systems (Singapore: Springer), 226–241. 10.1007/978-981-97-2257-9_17

  • CrossRef
  • Google Scholar

• 255

  WangY.LuW.LinM. B.RenR.HärdleW. K. (2024b). Cross-exchange crypto risk: a high-frequency dynamic network perspective. Int. Rev. Financial Analysis94, 103246. 10.1016/j.irfa.2024.103246

  • CrossRef
  • Google Scholar

• 256

  WątorekM.DrożdżS.KwapieńJ.MinatiL.OświęcimkaP.StanuszekM. (2020). Multiscale characteristics of the emerging global cryptocurrency market. Chaos, Solit. and Fractals136, 110037. 10.1016/j.chaos.2020.110037

  • CrossRef
  • Google Scholar

• 257

  WegerV.GassnerN.RosenthalJ. (2022). A survey on code-based cryptography. arXiv Prepr. arXiv:2201.07119. 10.48550/arXiv.2201.07119

  • CrossRef
  • Google Scholar

• 258

  WeichbrothP.WereszkoK.AnackaH.KowalJ. (2023). Security of cryptocurrencies: a view on the state-of-the-art research and current developments. Sensors23, 3155. 10.3390/s23063155

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 259

  World.org (2023). History of cryptocurrency: the idea, journey, and evolution. World.org Learn Cent. Crypto 101. 8-minute Read.

  • Google Scholar

• 260

  XiaP.SunX.ShiL.WuL.DuX. (2020). A differentially private greedy decision forest classification algorithm with high utility. Comput. and Secur.96, 101930. 10.1016/j.cose.2020.101930

  • CrossRef
  • Google Scholar

• 261

  XiongX.LuoJ. (2024). Global trends in cryptocurrency regulation: an overview. 71, 92. 10.1007/978-3-031-68974-1_4

  • CrossRef
  • Google Scholar

• 262

  XuJ.ParuchK.CousaertS.FengY. (2023). Sok: decentralized exchanges (dex) with automated market maker (amm) protocols. ACM Comput. Surv.55, 1–50. 10.1145/3570639

  • CrossRef
  • Google Scholar

• 263

  YangY.YuanH.YanL.RuanY. (2023). Post-quantum identity-based authenticated multiple key agreement protocol. ETRI J.45, 1090–1102. 10.4218/etrij.2022-0320

  • CrossRef
  • Google Scholar

• 264

  YiH. (2022). Secure social internet of things based on post-quantum blockchain. IEEE Trans. Netw. Sci. Eng.9, 950–957. 10.1109/TNSE.2021.3095192

  • CrossRef
  • Google Scholar

• 265

  ZaouiM.YousraB.YassineS.YassineM.KarimO. (2024). A comprehensive taxonomy of social engineering attacks and defense mechanisms: toward effective mitigation strategies. IEEE Access12, 72224–72241. 10.1109/ACCESS.2024.3403197

  • CrossRef
  • Google Scholar

• 266

  ZengP.BandyopadhyayD.Méndez MéndezJ. A.BitnerN.KolarA.SolomonM. T. (2024). Practical hybrid pqc-qkd protocols with enhanced security and performance. arXiv Prepr. arXiv:2411, 01086. 10.48550/arXiv.2411.01086

  • CrossRef
  • Google Scholar

• 267

  ZewdieM.GirmaA.SitoteT. (2024). A comprehensive review of insider threats and social engineering attacks detection: challenges, gaps, and a deep learning-based solution. Available online at: https://ssrn.com/abstract=4731400.SSRNPreprint.

  • Google Scholar

• 268

  ZhangR.XueR.LiuL. (2019). Security and privacy on blockchain. ACM Comput. Surv.52, 1–34. 10.1145/3316481

  • CrossRef
  • Google Scholar

• 269

  ZhangZ.XuC.HanY. (2024). Privacy-preserving cryptocurrency with threshold authentication and regulation. IEEE Trans. Inf. Forensics Secur.19, 6620–6635. 10.1109/TIFS.2024.3419694

  • CrossRef
  • Google Scholar

• 270

  ZhengZ. (2022). “Lattice-based cryptography,” in Modern cryptography volume 1: a classical introduction to informational and mathematical principles (Singapore: Springer), 253–351. 10.1007/978-981-16-5047-5_6

  • CrossRef
  • Google Scholar

• 271

  ZhouZ.ShenB. (2022). Toward understanding the use of centralized exchanges for decentralized cryptocurrency. Available online at: https://arxiv.org/ftp/arxiv/papers/2204/2204.08664.pdf.

  • Google Scholar

• 272

  ZhouF.ChenY.ZhuC.JiangL.LiaoX.ZhongZ.et al (2023). Visual analysis of money laundering in cryptocurrency exchange. IEEE Trans. Comput. Soc. Syst.11, 731–745. 10.1109/tcss.2022.3231687

  • CrossRef
  • Google Scholar