发表机构
Istanbul Technical University; Zurich University of Applied Sciences (ZHAW)（伊斯坦布尔理工大学; 苏黎世应用科学大学（ZHAW））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文系统综述边缘赋能物联网中的信任管理，提出跨架构层与领域分类体系，分析信任设计、集成及攻击，指出研究空白并展望上下文感知自适应信任管理方向。
AI 中文摘要
为人类生活和工业提供自主智能、普适连接和可用性，催生了物联网（IoT）的出现。为了支持对时间敏感和资源受限的应用，当今的物联网系统日益依赖边缘计算。这使计算和决策更接近终端设备。在边缘赋能的物联网架构中，延迟和通信开销得以降低，但也引入了更大且更多样化的设备、边缘节点、服务和数据源之间的交互。在此类环境中，安全和隐私机制提供了保护的基础，而信任管理可以评估交互实体的可靠性并调整安全决策。在本文中，我们系统地回顾了边缘赋能物联网中信任管理的现状。为此，我们提出了一个全面的分类体系，将物理、网络和应用架构物联网层映射到消费、商业、工业和基础设施物联网领域。我们进一步基于信任设计、信任如何集成到安全的物联网操作中以及影响信任管理过程的攻击，研究了最新研究。基于这些发现，我们识别了当前研究中的关键空白，并概述了边缘赋能物联网中上下文感知和自适应信任管理的未来方向。
英文摘要
Providing autonomous intelligence, pervasive connectivity and usability to human life and industry has led to the emergence of the Internet of Things (IoT). To support time-sensitive and resource-constrained applications, IoT systems nowadays increasingly rely on edge computing. This brings computation and decision-making closer to end devices. In edge-enabled IoT architecture, latency and communication overhead are reduced, but interactions among a larger and more diverse set of devices, edge nodes, services, and data sources are introduced as well. In such environments, security and privacy mechanisms provide the foundation for protection, while trust management can assess the reliability of interacting entities and adapting secure decisions. In this paper, we systematically review the current state of trust management in edge-enabled IoT. To this end, we propose a comprehensive taxonomy that maps physical, network, and application architectural IoT layers against the consumer, commercial, industrial, and infrastructure IoT domains. We further investigate state-of-art research based on their trust design, how trust integrated into secure IoT operations, the attacks that effect trust management process. Based on these findings, we identify key gaps in current research and outline future directions for context-aware and adaptive trust management in edge-enabled IoT.
Comments34+ pages, 9 figures, 12 tables, submitted and under review in ACM Computing Surveys
