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Decentralised Trust and Security Mechanisms for IoT Networks at the Edge: A Comprehensive Review

arXiv Security Archived Apr 21, 2026 ✓ Full text saved

arXiv:2604.17179v1 Announce Type: new Abstract: INTRODUCTION: The proliferation of the amalgamation of IoT and edge computing has increased the demand for decentralised trust and security mechanisms capable of operating across heterogeneous and resource-limited devices. Approaches such as federated learning, Zero Trust architectures, lightweight blockchain and distributed neural models offer alternatives to centralised control. OBJECTIVES: This review examines various state-of-the-art decentrali

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    Computer Science > Cryptography and Security [Submitted on 19 Apr 2026] Decentralised Trust and Security Mechanisms for IoT Networks at the Edge: A Comprehensive Review Khandoker Ashik Uz Zaman, Mahdi H. Miraz, Mohammed N. M. Ali INTRODUCTION: The proliferation of the amalgamation of IoT and edge computing has increased the demand for decentralised trust and security mechanisms capable of operating across heterogeneous and resource-limited devices. Approaches such as federated learning, Zero Trust architectures, lightweight blockchain and distributed neural models offer alternatives to centralised control. OBJECTIVES: This review examines various state-of-the-art decentralised mechanisms and evaluates their effectiveness in terms of securing IoT networks at the edge. METHODS: Thirty recent studies were analysed to compare how decentralised architectures establish trust, support secure communication and enable intrusion and anomaly detection. Frameworks, such as DFGL-LZTA, SecFedDNN and COSIER were assessed. RESULTS: Decentralised designs enhance privacy, reduce single points of failure and improve adaptive threat response, though challenges remain in scalability, efficiency and interoperability. CONCLUSION: The study identifies key considerations and future research needs for building secure and resilient trust-aware IoT edge ecosystems. Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI); Networking and Internet Architecture (cs.NI) Cite as: arXiv:2604.17179 [cs.CR]   (or arXiv:2604.17179v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2604.17179 Focus to learn more Journal reference: EAI Endorsed Trans IoT [Internet]. 2026 Mar. 31 [cited 2026 Apr. 19];11 Related DOI: https://doi.org/10.4108/eetiot.10996 Focus to learn more Submission history From: Khandoker Ashik Uz Zaman [view email] [v1] Sun, 19 Apr 2026 00:39:15 UTC (1,219 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.AI cs.NI References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Apr 21, 2026
    Archived
    Apr 21, 2026
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