Adversarial Attacks and Defenses in Deep Learning

• Published in: Engineering (Beijing, China) Vol. 6; no. 3; pp. 346 - 360
• Main Authors: Ren, Kui, Zheng, Tianhang, Qin, Zhan, Liu, Xue
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2020; College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China%Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 2E8, Canada%School of Computer Science, McGill University, Montreal, QC H3A 0E9, Canada; Institute of Cyberspace Research, Zhejiang University, Hangzhou 310027, China; Elsevier
• Subjects: Adversarial attack; Adversarial defense; Adversarial example; Deep neural network; Machine learning; Adversarial example; Deep neural network; Adversarial defense; Adversarial attack; Machine learning

With the rapid developments of artificial intelligence (AI) and deep learning (DL) techniques, it is critical to ensure the security and robustness of the deployed algorithms. Recently, the security vulnerability of DL algorithms to adversarial samples has been widely recognized. The fabricated samp...