Practical codes for the Gaussian wiretap channel are designed aiming at satisfying information-theoretic metrics to ensure security against a passive eavesdropper (Eve). Specifically, a design criterion is introduced for the coset coding scheme in order to satisfy a strong secrecy condition described with the mutual information between the secret message and Eve's observation. In addition, mutual information neural estimation (MINE) powered from deep learning tools is applied in order to directly compute the information-theoretic security constraint, and verify the proposed solutions. It is shown that finite-length coset codes can indeed ensure secure transmission from an information-theoretic perspective.

中文翻译：

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基于有限长度代码的高斯窃听通道安全通信


高斯窃听通道的实用代码旨在满足信息论指标，以确保针对被动窃听者 (Eve) 的安全性。具体来说，为陪集编码方案引入了设计准则，以满足用秘密消息和Eve观察之间的互信息描述的强保密条件。此外，应用由深度学习工具支持的互信息神经估计（MINE）来直接计算信息论安全约束，并验证所提出的解决方案。结果表明，从信息论的角度来看，有限长度陪集码确实可以确保安全传输。