Privacy-Aware Design of Distributed MIMO ISAC Systems

Abstract

Integrated Sensing and Communication (ISAC) systems raise unprecedented challenges regarding security and privacy since related applications involve the gathering of sensitive, identifiable information about people and the environment, which can lead to privacy leakage. Privacy-aware measures can steer the design of ISAC systems to prevent privacy violations. Thus, we explore this perspective for the design of distributed massive multiple-input multiple-output ISAC systems. For this purpose, we introduce an adversarial model where a malicious user exploits the interference from ISAC signals to extract sensing information. To mitigate this threat, we propose an iterative privacy-aware framework of two blocks: precoder design and access point selection. The precoder design aims to minimize the mutual information between the sensing and communication signals by imposing constraints on sensing and communication performance and maximum transmit power. The access point selection also aims to minimize the mutual information between communication and sensing signals by strategically selecting access points that transmit ISAC signals, and sensing receivers. Results show a reduction in the effectiveness of the attack measured by the probability of detection of the attacker.