Generative AI Meets Semantic Communications: Opportunities, Challenges and Security Risks

Pengfei Ren, Jingjing Wang, Jianrui Chen, Xiangwang Hou, Haohua Du, Chunxiao Jiang

Abstract: Semantic communication (SC) leverages artificial intelligence (AI) to extract task-relevant semantic information based on specific requirements, enabling more efficient communication, which is regarded as one of the critical components for future 6G intelligent networks. Meanwhile, generative AI (GAI), a significant technological breakthrough in recent years, is renowned for its semantic extraction capabilities and data generation creativity. Inspired by this, in this paper, we explore the integration of GAI into SC, focusing on technological intersection and security risks. We begin with a comprehensive overview of SC and GAI, analyzing the current challenges. Subsequently, we elaborate on how GAI can optimize SC from multiple perspectives, including semantic extraction, data transmission, and cloud-edge deployment. In particular, we focus on security and privacy issues within the GAI-enhanced SC architecture. Finally, we validate the feasibility of our theory through a case study and outline potential directions for future research.

External IDs:dblp:journals/network/RenWCHDJ25