Feb. 28, 2024, 5:11 a.m. | Robert L. Bassett, Austin Van Dellen, Anthony P. Austin

cs.CR updates on arXiv.org arxiv.org

arXiv:2402.17104v1 Announce Type: cross
Abstract: We investigate the vulnerability of computer-vision-based signal classifiers to adversarial perturbations of their inputs, where the signals and perturbations are subject to physical constraints. We consider a scenario in which a source and interferer emit signals that propagate as waves to a detector, which attempts to classify the source by analyzing the spectrogram of the signal it receives using a pre-trained neural network. By solving PDE-constrained optimization problems, we construct interfering signals that cause the …

adversarial arxiv computer constraints cs.cr cs.lg detector eess.sp inputs math.oc physical scenario signal signals stat.ml the source vulnerability

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