A Superposition Code-Based Semantic Communication Approach with Quantifiable and Controllable Security

TL;DR

This paper introduces a superposition code-based semantic communication method that provides quantifiable and controllable security, ensuring eavesdroppers receive nearly random data while legitimate receivers decode accurately, outperforming existing techniques.

Contribution

The work proposes a novel superposition coding scheme with a double-layered constellation for secure semantic communication, achieving quantifiable security and robustness against eavesdroppers.

Findings

Eavesdropper's SEP approaches random guessing, ensuring security.

Legitimate receiver maintains low SEP for accurate decoding.

Method outperforms benchmark techniques in security and robustness.

Abstract

This paper addresses the challenge of achieving security in semantic communication (SemCom) over a wiretap channel, where a legitimate receiver coexists with an eavesdropper experiencing a poorer channel condition. Despite previous efforts to secure SemCom against eavesdroppers, guarantee of approximately zero information leakage remains an open issue. In this work, we propose a secure SemCom approach based on superposition code, aiming to provide quantifiable and controllable security for digital SemCom systems. The proposed method employs a double-layered constellation map, where semantic information is associated with satellite constellation points and cloud center constellation points are randomly selected. By carefully allocating power between these two layers of constellation, we ensure that the symbol error probability (SEP) of the eavesdropper when decoding satellite constellation points is nearly equivalent to random guessing, while maintaining a low SEP for the legitimate receiver to successfully decode the semantic information. Simulation results demonstrate that the peak signal-to-noise ratio (PSNR) and mean squared error (MSE) of the eavesdropper's reconstructed data, under the proposed method, can range from decoding Gaussian-distributed random noise to approaching the variance of the data. This validates the effectiveness of our method in nearly achieving the experimental upper bound of security for digital SemCom systems when both eavesdroppers and legitimate users utilize identical decoding schemes. Furthermore, the proposed method consistently outperforms benchmark techniques, showcasing superior data security and robustness against eavesdropping. The implementation code is publicly available at: https://github.com/1weixuanchen/ A-Superposition-Code-Based-Semantic-Communication.