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Versatile Weight Attack via Flipping Limited Bits. (arXiv:2207.12405v1 [cs.CR])
July 27, 2022, 1:20 a.m. | Jiawang Bai, Baoyuan Wu, Zhifeng Li, Shu-tao Xia
cs.CR updates on arXiv.org arxiv.org
To explore the vulnerability of deep neural networks (DNNs), many attack
paradigms have been well studied, such as the poisoning-based backdoor attack
in the training stage and the adversarial attack in the inference stage. In
this paper, we study a novel attack paradigm, which modifies model parameters
in the deployment stage. Considering the effectiveness and stealthiness goals,
we provide a general formulation to perform the bit-flip based weight attack,
where the effectiveness term could be customized depending on the attacker's …
More from arxiv.org / cs.CR updates on arXiv.org
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