Adversarial Perturbation Defense on Deep Neural Networks

Deep neural networks (DNNs) have been verified to be easily attacked by well-designed adversarial perturbations. Image objects with small perturbations that are imperceptible to human eyes can induce DNN-based image class classifiers towards making erroneous predictions with high probability. Advers...

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Bibliographic Details
Published in:ACM computing surveys 2022-11, Vol.54 (8), p.1-36, Article 159
Main Authors: Zhang, Xingwei, Zheng, Xiaolong, Mao, Wenji
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Artificial neural networks
Computer science
Computing methodologies
Machine learning
Malware and its mitigation
Neural networks
Perturbation
Security and privacy
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