Eavesdropping has been a long-standing threat to the security and privacy of wireless communications, since it is difficult to detect and costly to prevent. As networks evolve towards Sixth Generation (6G) and semantic communication becomes increasingly central to next-generation wireless systems, securing semantic information transmission emerges as a critical challenge. While classical physical layer security (PLS) focuses on passive security, the recently proposed concept of physical layer deception (PLD) offers a semantic encryption measure to actively deceive eavesdroppers. Yet the existing studies of PLD have been dominantly information-theoretical and link-level oriented, lacking considerations of system-level design and practical implementation. In this work we propose Visual ENcryption for Eavesdropping NegAtion (VENENA), an artificial intelligence-enabled framework for secure image-based communication. VENENA protects confidential messages by encoding them visually while actively deceiving eavesdroppers: legitimate receivers use artificial intelligence (AI)-based classifiers to extract true message semantics, while interceptors perceive only falsified content. The framework transmits two superimposed image components with different power levels - a high-power decoy image and a low-power correction mask - ensuring only authorized receivers with favorable channel conditions can reconstruct the true message. Experimental validation demonstrates over 93% accuracy for legitimate users while limiting eavesdropper success to 52% even when system design is fully known, validating VENENA's active defense capability for 6G semantic communication.

翻译：窃听一直是无线通信安全与隐私面临的长期威胁，因其难以检测且防范成本高昂。随着网络向第六代（6G）演进，语义通信在下一代无线系统中的重要性日益凸显，保障语义信息传输安全成为关键挑战。传统物理层安全主要关注被动防护，而近期提出的物理层欺骗概念为实现主动欺骗窃听者提供了语义加密手段。然而现有物理层欺骗研究主要集中于信息论与链路层面，缺乏系统级设计与实际部署考量。本文提出面向窃听抵制的视觉加密框架VENENA，这是一种基于人工智能的安全图像通信框架。VENENA通过视觉编码保护机密信息并主动欺骗窃听者：合法接收者使用基于人工智能的分类器提取真实语义，而拦截者仅能感知伪造内容。该框架通过叠加传输两个不同功率等级的图像分量——高功率诱饵图像与低功率校正掩码，确保仅信道条件优越的授权接收方能重构真实信息。实验验证表明，合法用户解码准确率超过93%，而即使系统设计完全暴露时窃听成功率仍被限制在52%，证实了VENENA在6G语义通信中的主动防御能力。