智能窃听码设计：结合信息论与深度学习挖掘无线内生安全潜力
Intelligent Wiretap Code Design: Exploiting Wireless Endogenous Security via Information Theory and Deep Learning Integration
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中文总结 AI 辅助
本文在语义通信框架下提出窃听编码方案，针对两类窃听场景分别用互信息、广义互信息指导编码优化，以利用无线内生随机性提升通信安全与可靠性。
中文摘要 AI 辅助
无线内生安全领域的最新进展已探索利用无线信道的固有随机性提升通信安全性，为传统加密方法提供了有效替代方案。本文在语义通信框架内提出一种窃听编码方案，该方案利用与常规数字调制兼容的离散语义表示，共同提升通信安全性与可靠性。我们研究两种窃听场景：（i）窃听者采用最大后验概率（MAP）解码器；（ii）窃听者拥有与合法接收者相同的解码器。在第一种场景中，我们将互信息作为度量来指导优化编码策略的设计，以最小化信息泄漏同时提升通信可靠性；在第二种场景中，考虑到窃听者解码能力的限制，我们采用广义互信息（GMI）来表征规定解码规则下的可恢复性，并指导感知可靠性的码优化。
英文摘要
Recent advancements in wireless endogenous security have explored leveraging the inherent randomness of wireless channels to enhance communication security, providing an effective alternative to traditional encryption methods. This paper proposes a wiretap coding scheme within the semantic communication framework, which leverages discrete semantic representations compatible with conventional digital modulation to jointly enhance communication security and reliability. We investigate two eavesdropping scenarios: (i) the eavesdropper employs a maximum a posteriori (MAP) decoder, and (ii) the eavesdropper has access to a decoder identical to that of the legitimate receiver. In the first scenario, we exploit mutual information as a metric to guide the design of an optimized coding strategy, minimizing information leakage while enhancing communication reliability. In the second scenario, considering the limitations of the eavesdropper's decoding capability, we employ generalized mutual information (GMI) to characterize recoverability under the prescribed decoding rule and guide reliability-aware code optimization.
