Attack Anything: Blind DNNs via Universal Background Adversarial Attack

It has been widely substantiated that deep neural networks (DNNs) are susceptible and vulnerable to adversarial perturbations. Existing studies mainly focus on performing attacks by corrupting targeted objects (physical attack) or images (digital attack), which is intuitively acceptable and understa...

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Hauptverfasser:	Lian, Jiawei, Mei, Shaohui, Wang, Xiaofei, Wang, Yi, Wang, Lefan, Lu, Yingjie, Ma, Mingyang, Chau, Lap-Pui
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Cryptography and Security Computer Science - Learning
Online-Zugang:	Volltext bestellen
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