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Anti-Malicious ISAC Using Proactive Monitoring

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arxiv 2410.04408 v1 pith:KV7IUKZ7 submitted 2024-10-06 cs.IT eess.SPmath.IT

classification cs.ITeess.SPmath.IT
keywords malicioussensingisacmonitormonitoringproactivesinractivities
verification ladder T0 review T1 audit T2 compute T3 formal
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In this paper, we investigate proactive monitoring to mitigate malicious activities in integrated sensing and communication (ISAC) systems. Our focus is on a scenario where a cell-free massive multiple-input multiple-output (CF-mMIMO) architecture is exploited by malicious actors. Malicious actors use multiple access points (APs) to illegally sense a legitimate target while communicating with users (UEs), one of which is suspected of illegal activities. In our approach, a proactive monitor overhears the suspicious UE and simultaneously sends a jamming signal to degrade the communication links between the APs and suspicious UE. Simultaneously, the monitor sends a precoded jamming signal toward the legitimate target to hinder the malicious sensing attempts. We derive closed-form expressions for the sensing signal-to-interference-noise ratio (SINR), as well as the received SINR at the UEs and overheard SINR at the monitor. The simulation results show that our anti-malicious CF-mMIMO ISAC strategy can significantly reduce the sensing performance while offering excellent monitoring performance.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. How to Proactively Monitor Untrusted Communications with Cell-Free Massive MIMO?

    eess.SP 2025-08 unverdicted novelty 6.0 of 10

    A cell-free massive MIMO monitoring network with MMSE channel estimation and Bayesian-optimized jamming and mode selection can disrupt untrusted communications with success probability above 0.8.

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