Semantic communication, emerging as a breakthrough beyond the classical Shannon paradigm, aims to convey the essential meaning of source data rather than merely focusing on precise yet content-agnostic bit transmission. By interconnecting diverse intelligent agents (e.g., autonomous vehicles and VR devices) via semantic communications, the semantic communication networks (SemComNet) supports semantic-oriented transmission, efficient spectrum utilization, and flexible networking among collaborative agents. Consequently, SemComNet stands out for enabling ever-increasing intelligent applications, such as autonomous driving and Metaverse. However, being built on a variety of cutting-edge technologies including AI and knowledge graphs, SemComNet introduces diverse brand-new and unexpected threats, which pose obstacles to its widespread development. Besides, due to the intrinsic characteristics of SemComNet in terms of heterogeneous components, autonomous intelligence, and large-scale structure, a series of critical challenges emerge in securing SemComNet. In this paper, we provide a comprehensive and up-to-date survey of SemComNet from its fundamentals, security, and privacy aspects. Specifically, we first introduce a novel three-layer architecture of SemComNet for multi-agent interaction, which comprises the control layer, semantic transmission layer, and cognitive sensing layer. Then, we discuss its working modes and enabling technologies. Afterward, based on the layered architecture of SemComNet, we outline a taxonomy of security and privacy threats, while discussing state-of-the-art defense approaches. Finally, we present future research directions, clarifying the path toward building intelligent, robust, and green SemComNet. To our knowledge, this survey is the first to comprehensively cover the fundamentals of SemComNet, alongside a detailed analysis of its security and privacy issues.

翻译：语义通信作为超越经典香农范式的突破性技术，其目标在于传递源数据的本质含义，而非仅关注精确但与内容无关的比特传输。通过语义通信互联各类智能体（如自动驾驶车辆和虚拟现实设备），语义通信网络支持面向语义的传输、高效的频谱利用以及协作智能体间的灵活组网。因此，语义通信网络在赋能自动驾驶、元宇宙等日益增长的智能应用方面脱颖而出。然而，由于构建于人工智能和知识图谱等多元前沿技术之上，语义通信网络引入了各类全新且不可预见的威胁，为其广泛部署带来了障碍。此外，考虑到语义通信网络在异构组件、自主智能和大规模结构方面的固有特性，保障其安全面临一系列关键挑战。本文从基本原理、安全与隐私角度对语义通信网络进行了全面且最新的综述。具体而言，我们首先针对多智能体交互提出了一种包含控制层、语义传输层和认知感知层的新型三层语义通信网络架构；随后探讨了其工作模式与支撑技术；接着，基于该分层架构，我们梳理了安全与隐私威胁的分类体系，并讨论了现有先进防御方法。最后，我们展望了未来研究方向，为构建智能、鲁棒且绿色的语义通信网络指明了路径。据我们所知，本综述首次全面覆盖了语义通信网络的基本原理，并对其安全与隐私问题进行了深入分析。