Securing ISAC Against Pilot Spoofing Attack: A Deep Plug-and-Play Countermeasure

Abstract

In this letter, we propose a deep plug-and-play prior approach for designing a robust integrated sensing and communication (ISAC) precoder that combats the pilot spoofing attack for the first time. Specifically, our precoder design is formulated as a robust optimization problem that maximizes the sensing power while minimizing the eavesdropping signal-to-interference-plus-noise ratio simultaneously, even without the need for knowledge of the victim’s and eavesdropper’s channel state information. To address this challenging design problem, a deep learning network is exploited to minimize the information leakage, which is subsequently integrated and plugged in as a modular component into an iterative precoder optimization algorithm, under a communication constraint. Simulation results confirm the secrecy performance of our proposed deep prior induced ISAC precoder design approach.