用对抗性网络实现通信感知一体化的安全增强
Security-aware Semantic-driven ISAC via Paired Adversarial Residual Networks
- 设计成对的可插拔加密解密模块，基于可训练对抗残差网络
- 联合优化使通信感知性能与防窃听能力同时提升
- 灵活部署无需改硬件，适合高安全需求系统
本文提出一种新型灵活的安全感知语义驱动集成感知与通信（ISAC）框架——安全语义ISAC（SS-ISAC）。受对抗攻击正向影响启发，设计了一对可插拔的加密与解密模块。加密模块置于语义发射端后，采用可训练的对抗残差网络（ARN）生成对抗攻击；解密模块置于语义接收端前，使用另一可训练的ARN以缓解对抗攻击和噪声。两个模块可根据系统安全需求灵活组合，无需大幅改动硬件。为在保障感知与通信（SAC）性能的同时防范窃听威胁，上述ARN通过最小化一个精心设计的损失函数进行联合优化，该函数关联对抗攻击强度、SAC性能及隐私泄露风险。仿真结果验证了所提SS-ISAC框架在SAC性能与防窃听能力方面的有效性。
原文摘要 · Abstract (English)
This paper proposes a novel and flexible security-aware semantic-driven integrated sensing and communication (ISAC) framework, namely security semantic ISAC (SS-ISAC). Inspired by the positive impact of the adversarial attack, a pair of pluggable encryption and decryption modules is designed in the proposed SS-ISAC framework. The encryption module is installed after the semantic transmitter, adopting a trainable adversarial residual network (ARN) to create the adversarial attack. Correspondingly, the decryption module before the semantic receiver utilizes another trainable ARN to mitigate the adversarial attack and noise. These two modules can be flexibly assembled considering the system security demands, without drastically modifying the hardware infrastructure. To ensure the sensing and communication (SAC) performance while preventing the eavesdropping threat, the above ARNs are jointly optimized by minimizing a carefully designed loss function that relates to the adversarial attack power, SAC performance, as well as the privacy leakage risk. Simulation results validate the effectiveness of the proposed SS-ISAC framework in terms of both SAC and eavesdropping prevention performance.
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