Securing the Edge: Cybersecurity for IoT and Distributed Systems

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About this Research Topic

Submission deadlines

  1. Manuscript Summary Submission Deadline 18 January 2026 | Manuscript Submission Deadline 8 May 2026

  2. This Research Topic is currently accepting articles.

Background

The Internet of Things represents a shift in the architecture of our digital world, embedding computational intelligence into the physical fabric of our lives. From smart homes and wearable devices to industrial sensors and autonomous systems, billions of interconnected devices are generating an unprecedented stream of data. Traditionally, this data was sent to centralized cloud data centers for processing and storage. However, the sheer volume of data, coupled with the critical need for ultra-low latency and bandwidth efficiency in applications like autonomous driving and real-time industrial automation, has exposed the limitations of this cloud-dependent model. A new computing paradigm as Edge Computing decentralizes the cloud by pushing data processing, storage, and analytics closer to the source of data generation in the "edge" of the network. Research in this area is not merely an extension of existing IT security but requires a foundational rethinking of principles to secure the future of our connected world.

Security in WSN and Internet of Things aims to collate cutting-edge research and innovative solutions that address the multifaceted security, privacy, and trust challenges inherent in distributed IoT ecosystems. This Special Issue aims to serve as a definitive reference point, fostering interdisciplinary dialogue and presenting a curated collection of breakthroughs that will lay the groundwork for a robust, secure, and trustworthy intelligent edge ecosystem. We invite the community to contribute to this essential endeavor.

We welcome articles addressing, but not limited to, the following themes:

- Intrusion Detection and Prevention at the Edge: AI and machine learning-based anomaly detection systems, collaborative threat intelligence sharing, and lightweight Intrusion Detection Systems (IDS) for edge networks.

- Privacy-Preserving Computing in Distributed IoT: Techniques such as federated learning, differential privacy, and secure multi-party computation implemented at the edge to protect user data.

- Opportunities and Challenges: Exploring secure, efficient, and interoperable solutions to enable resilient, intelligent, and sustainable IoT and edge computing ecosystems.

- Security of Edge-to-Cloud Continuum: Vulnerabilities and security protocols for data in transit and at rest across the entire data pipeline, from sensor to cloud.

- Resilience and Survivability: Strategies for building self-healing, fault-tolerant, and resilient IoT systems that can maintain operation even under attack.

- Hardware-Oriented Security: Physical Unclonable Functions (PUFs), trusted execution environments (TEEs), and side-channel attack mitigation for edge devices.

- Case Studies and Threat Modeling: Real-world security analyses, vulnerability assessments, and novel threat models for specific edge-IoT applications (e.g., smart grids, connected health, industrial control systems).

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  • Mini Review

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Keywords: Edge-Computing, IoT, WSN, Cibersecurity, Distributed Systems, Privacy-Preserving Machine Learning, Security and Privacy, Trusted Execution Environments (TEE), Resilience in IoT

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