Decentralised Trust and Security Mechanisms for IoT Networks at the Edge: A Comprehensive Review
DOI:
https://doi.org/10.4108/eetiot.10996Keywords:
Decentralised Security, Federated Learning, Zero Trust Architecture, Trust Management, IoT, Edge Computing, Intrusion Detection, Distributed SystemsAbstract
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.
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Copyright (c) 2026 Khandoker Ashik Uz Zaman, Mahdi H. Miraz, Mohammed N. M. Ali
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