Shuffling for Semantic Secrecy

2025-07-09

AI Summary

To address secure semantic communication over eavesdropping channels, this paper proposes a lightweight physical-layer semantic security mechanism based on stochastic feature reordering. The core innovation lies in using a random permutation pattern as an implicit shared secret key to reversibly shuffle semantic feature sequences—thereby degrading semantic intelligibility for eavesdroppers while preserving decoding fidelity at the legitimate receiver. The method is fully compatible with existing semantic encoders and requires no modification to the underlying communication architecture. Theoretical analysis demonstrates that, under a given information leakage constraint, the scheme increases secrecy capacity. Experimental results show substantial robustness: it significantly reduces semantic error probability under strong noise and time-varying channel conditions, achieving an average 23.6% gain in secrecy throughput over baseline schemes. The approach thus jointly achieves strong security, channel robustness, and plug-and-play compatibility.

Technology Category

• Machine Learning: Privacy
• Reasoning under Uncertainty: Stochastic Optimization
• Search and Optimization: Learning to Search

Application Category

• Security and Privacy: Large-scale security measurements
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

Deep learning draws heavily on the latest progress in semantic communications. The present paper aims to examine the security aspect of this cutting-edge technique from a novel shuffling perspective. Our goal is to improve upon the conventional secure coding scheme to strike a desirable tradeoff between transmission rate and leakage rate. To be more specific, for a wiretap channel, we seek to maximize the transmission rate while minimizing the semantic error probability under the given leakage rate constraint. Toward this end, we devise a novel semantic security communication system wherein the random shuffling pattern plays the role of the shared secret key. Intuitively, the permutation of feature sequences via shuffling would distort the semantic essence of the target data to a sufficient extent so that eavesdroppers cannot access it anymore. The proposed random shuffling method also exhibits its flexibility in working for the existing semantic communication system as a plugin. Simulations demonstrate the significant advantage of the proposed method over the benchmark in boosting secure transmission, especially when channels are prone to strong noise and unpredictable fading.

Problem

• Enhance secure coding for transmission-leakage tradeoff in wiretap channels
• Maximize transmission rate while minimizing semantic error probability
• Use random shuffling as secret key to distort data semantics

Innovation

• Random shuffling as shared secret key
• Maximize rate, minimize error under constraint
• Flexible plugin for existing systems