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ORIGINAL RESEARCH article

Front. Phys.

Sec. Social Physics

This article is part of the Research TopicSecurity, Governance, and Challenges of the New Generation of Cyber-Physical-Social Systems, Volume IIView all 19 articles

A Side-Channel Attack for Recovering Keys in HMAC-SM3 Algorithm

Provisionally accepted
Zhen  WuZhen Wu1*Zhiguang  QinZhiguang Qin1Kai  WangKai Wang2
  • 1University of Electronic Science and Technology of China, Chengdu, China
  • 2CHINA MERCHANTS GROUP TESTING & CERTIFICATION (CHONGQING) CO. LTD, Chongqing, China

The final, formatted version of the article will be published soon.

Cyber-Physical-Social Systems(CPSS) face growing side-channel threats, compromising secure data transmission and authentication. As China's national cryptographic hash standard, SM3 is widely used in these systems for identity and data integrity, yet its key-dependent input vulnerabilities remain insufficiently tackled, particularly those exploitable through side-channel attacks. This study addresses critical limitations of traditional side-channel attacks for HMAC-SM3 key recovery: non-profiling approaches fail due to the absence of exploitable plaintext correlations, while profiling-based methods suffer from error accumulation and achieve extremely low success rates in single-trace scenarios . To overcome these bottlenecks, we propose a novel self-calibrating side-channel attack that enables high-accuracy key input recovery for HMAC-SM3 using only a single power trace. The method constructs a Bayesian network to integrate power consumption trace statistics with prior knowledge of input dependencies, employing belief propagation for joint probabilistic inference. The experimental tests showed that key recovery achieved 100% success under simulated noiseless conditions, a success rate of 91.45% on a real smart card system, and remained 73% effective at a signal-to-noise ratio of 10 dB. This paper identifies new security risks for key-bearing objects in Cyber-Physical-Social Systems and provides theoretical foundations for effective countermeasures.

Keywords: Bayesian network, cyber-physical-social system, HMAC-SM3, Message expansion, Probabilistic graphical model, self-calibrating side-channel attack

Received: 18 Aug 2025; Accepted: 03 Feb 2026.

Copyright: © 2026 Wu, Qin and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Zhen Wu

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