DefenseFea: An Input Transformation Feature Searching Algorithm Based Latent Space for Adversarial Defense

DefenseFea: An Input Transformation Feature Searching Algorithm Based Latent Space for Adversarial Defense

Deep neural networks based image classification systems could suffer from adversarial attack algorithms, which generate input examples by adding deliberately crafted yet imperceptible noise to original input images. These crafted examples can fool systems and further threaten their security. In this...

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Bibliographic Details
Main Authors:	Pan Zhang, Yangjie Cao, Chenxi Zhu, Yan Zhuang, Haobo Wang, Jie Li
Format:	Article
Language:	English
Published:	Sciendo 2024-02-01
Series:	Foundations of Computing and Decision Sciences
Subjects:	adversarial attack adversarial defense latent space adversarial training
Online Access:	https://doi.org/10.2478/fcds-2024-0002

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