Rethinking Secure Semantic Communications in the Age of Generative and Agentic AI: Threats and Opportunities

TL;DR

This paper examines the security and privacy challenges posed by generative and agentic AI in semantic communication systems, proposing a taxonomy of threats and exploring potential privacy-preserving solutions.

Contribution

It provides a comprehensive taxonomy of eavesdropping threats in SemCom and discusses how advanced AI can both threaten and enhance privacy protections.

Findings

GenAI enables powerful semantic decoding that can intercept private information.

Agentic AI allows adaptive inference, increasing privacy risks.

Opportunities exist to leverage AI for privacy-preserving SemCom designs.

Abstract

Semantic communication (SemCom) improves communication efficiency by transmitting task-relevant information instead of raw bits and is expected to be a key technology for 6G networks. Recent advances in generative AI (GenAI) further enhance SemCom by enabling robust semantic encoding and decoding under limited channel conditions. However, these efficiency gains also introduce new security and privacy vulnerabilities. Due to the broadcast nature of wireless channels, eavesdroppers can also use powerful GenAI-based semantic decoders to recover private information from intercepted signals. Moreover, rapid advances in agentic AI enable eavesdroppers to perform long-term and adaptive inference through the integration of memory, external knowledge, and reasoning capabilities. This allows eavesdroppers to further infer user private behavior and intent beyond the transmitted content. Motivated by these emerging challenges, this paper comprehensively rethinks the security and privacy of SemCom systems in the age of generative and agentic AI. We first present a systematic taxonomy of eavesdropping threat models in SemCom systems. Then, we provide insights into how GenAI and agentic AI can enhance eavesdropping threats. Meanwhile, we also highlight potential opportunities for leveraging GenAI and agentic AI to design privacy-preserving SemCom systems.