Yuetian Wang, Chuanjing Zhang, Xuxin Liao, Xingang Wang, Zhaoquan Gu*
Journal on Artificial Intelligence, Vol.3, No.1, pp. 1-8, 2021, DOI:10.32604/jai.2021.014175
Abstract Deep neural networks (DNNs) are widely adopted in daily life and the
security problems of DNNs have drawn attention from both scientific researchers
and industrial engineers. Many related works show that DNNs are vulnerable to
adversarial examples that are generated with subtle perturbation to original images
in both digital domain and physical domain. As a most common application of
DNNs, face recognition systems are likely to cause serious consequences if they
are attacked by the adversarial examples. In this paper, we implement an
adversarial attack system for face recognition in both digital domain that generates
adversarial face images to fool… More >
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