AI & ML
Physical Sensing Verification for Cognitive ISAC against UAV Spoofing via Digital Twins
arXiv eess.SP0 views
arXiv:2611.08658v1 Announce Type: new Abstract: As integrated sensing and communication (ISAC) lets 5G and 6G base stations detect drones, software agents will soon act on what they sense. This amplifies the threat of a relay replaying the base station's signal as a phantom drone. For such cognitive ISAC systems, this paper proposes a wall-based physical check. A digital twin (DT) predicts where a real target's wall echo must arrive; a relay can fake range, but not where its own reflections come from. The paper proves that line-of-sight beam steering cannot expose a matched relay, and that, under stated conditions, a single-antenna relay faking a wall echo leaves a telltale echo where a genuine target leaves none. In a pre-registered ray-tracing study, the twin's evidence separated genuine targets from replays perfectly (AUC 1.000) on held-out streets, and a later-registered passive check needing no extra transmission accepted every genuine target and no replay. The primary active probe was inconclusive, at 5.3\% false acceptances against a 5\% limit, for lack of threshold margin. At the evaluated relay positions, the conditional bound certifies 3 of 24 held-out streets, reproduced on fresh ones, against single-antenna relay signals meeting its conditions, adaptive or fixed, and 11 of 24 at double bandwidth.
Source:https://arxiv.org/abs/2611.08658PreviousClassification Aggregation with Multiple MembershipsNext13,000-Fold Frequency Down Conversion From 280 MHz to 21 kHz Using Mechanical Frequency Combs
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