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ObfuNAS: A Neural Architecture Search-based DNN Obfuscation Approach. (arXiv:2208.08569v2 [cs.CR] UPDATED)
Aug. 25, 2022, 1:20 a.m. | Tong Zhou, Shaolei Ren, Xiaolin Xu
cs.CR updates on arXiv.org arxiv.org
Malicious architecture extraction has been emerging as a crucial concern for
deep neural network (DNN) security. As a defense, architecture obfuscation is
proposed to remap the victim DNN to a different architecture. Nonetheless, we
observe that, with only extracting an obfuscated DNN architecture, the
adversary can still retrain a substitute model with high performance (e.g.,
accuracy), rendering the obfuscation techniques ineffective. To mitigate this
under-explored vulnerability, we propose ObfuNAS, which converts the DNN
architecture obfuscation into a neural architecture search …
More from arxiv.org / cs.CR updates on arXiv.org
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