Title: Learning-based Power Control for Secure Covert Semantic Communication Show Chinese title

Title: 基于学习的用于安全隐秘语义通信的功率控制

Abstract: Despite progress in semantic communication (SemCom), research on SemCom security is still in its infancy. To bridge this gap, we propose a general covert SemCom framework for wireless networks, reducing eavesdropping risk. Our approach transmits semantic information covertly, making it difficult for wardens to detect. Given the aim of maximizing covert SemCom performance, we formulate a power control problem in covert SemCom under energy constraints. Furthermore, we propose a learning-based approach based on the soft actor-critic algorithm, optimizing the power of the transmitter and friendly jammer. Numerical results demonstrate that our approach effectively enhances the performance of covert SemCom. Show Chinese abstract

Abstract: 尽管在语义通信（SemCom）方面取得了进展，但关于SemCom安全的研究仍处于初期阶段。 为了弥补这一差距，我们提出了一种通用的隐蔽SemCom框架，用于无线网络，以降低窃听风险。 我们的方法隐蔽地传输语义信息，使看守难以检测。 鉴于最大化隐蔽SemCom性能的目标，我们在能量约束下制定了隐蔽SemCom中的功率控制问题。 此外，我们提出了一种基于软演员-评论家算法的学习方法，优化发射机和友好干扰机的功率。 数值结果表明，我们的方法有效提高了隐蔽SemCom的性能。