Feb. 15, 2024, 5:42 a.m. | Dinuka Sahabandu, Xiaojun Xu, Arezoo Rajabi, Luyao Niu, Bhaskar Ramasubramanian, Bo Li, Radha Poovendran

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.08695v1 Announce Type: cross
Abstract: We propose and analyze an adaptive adversary that can retrain a Trojaned DNN and is also aware of SOTA output-based Trojaned model detectors. We show that such an adversary can ensure (1) high accuracy on both trigger-embedded and clean samples and (2) bypass detection. Our approach is based on an observation that the high dimensionality of the DNN parameters provides sufficient degrees of freedom to simultaneously achieve these objectives. We also enable SOTA detectors to …

abstract accuracy analyze arxiv cs.cr cs.lg detection dnn embedded game samples show sota type

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