综述边缘IoT网络去中心化信任与安全机制，助你快速掌握前沿方案。
Decentralised Trust and Security Mechanisms for IoT Networks at the Edge: A Comprehensive Review
- 对比30篇论文，分析去中心化架构如何建立信任
- 提升隐私保护，降低单点故障风险，增强威胁响应能力
- 适合关注边缘安全、分布式系统的研究者与工程师
物联网与边缘计算的融合催生了对跨异构、资源受限设备的去中心化信任与安全机制的需求。联邦学习、零信任架构、轻量级区块链和分布式神经网络模型等成为替代集中控制的可行方案。本文综述了最新去中心化机制，评估其在保障边缘IoT网络安全方面的有效性。基于30项近期研究，分析去中心化架构如何建立信任、支持安全通信并实现入侵与异常检测。评估框架包括DFGL-LZTA、SecFedDNN和COSIER。结果表明，去中心化设计可增强隐私保护，减少单点故障，提升自适应威胁响应能力，但仍在可扩展性、效率和互操作性方面面临挑战。研究识别出构建安全、弹性、可信感知的边缘IoT生态的关键考量与未来方向。
原文摘要 · Abstract (English)
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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