Semantic Communication Networks Empowered Artificial Intelligence of Things

TL;DR

This paper surveys the security and privacy challenges in semantic communication networks that enable AI of Things, highlighting threats and countermeasures to ensure secure, meaningful information exchange among diverse intelligent entities.

Contribution

It provides a comprehensive overview of security and privacy issues in semantic communication systems and discusses current countermeasures and open research directions.

Findings

Semantic communication faces significant security and privacy threats.

Current countermeasures include encryption, authentication, and trust management.

Open issues involve scalable security solutions and trust frameworks.

Abstract

Semantic communication aims to facilitate purposeful information exchange among diverse intelligent entities, including humans, machines, and organisms. It emphasizes precise semantic transmission over data fidelity, striving for meaningful expression while optimizing communication resources for efficient information transfer. Nevertheless, extant semantic communication systems face security, privacy, and trust challenges in integrating AI technologies for intelligent communication applications. This paper presents a comprehensive survey of security and privacy threats across various layers of semantic communication systems and discusses state-of-the-art countermeasures within both academic and industry contexts. Finally, we identify critical open issues in this burgeoning field warranting further investigation.