Deyin Li1, 2, Mingzhi Cheng3, Yu Yang1, 2, *, Min Lei1, 2, Linfeng Shen4
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 623-635, 2020, DOI:10.32604/cmc.2020.09800
Abstract Deep learning networks are widely used in various systems that require
classification. However, deep learning networks are vulnerable to adversarial attacks. The
study on adversarial attacks plays an important role in defense. Black-box attacks require
less knowledge about target models than white-box attacks do, which means black-box
attacks are easier to launch and more valuable. However, the state-of-arts black-box
attacks still suffer in low success rates and large visual distances between generative
adversarial images and original images. This paper proposes a kind of fast black-box
attack based on the cross-correlation (FBACC) method. The attack is carried out in two
stages.… More >
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