An Intelligent Secure Adversarial Examples Detection Scheme in Heterogeneous Complex Environments
Weizheng Wang,
Xiangqi Wang,
Xianmin Pan
et al.
Abstract:Image-denoising techniques are widely used to defend against Adversarial Examples (AEs). However, denoising alone cannot completely eliminate adversarial perturbations. The remaining perturbations tend to amplify as they propagate through deeper layers of the network, leading to misclassifications. Moreover, image denoising compromises the classification accuracy of original examples. To address these challenges in AE defense through image denoising, this paper proposes a novel AE detection technique. The prop… Show more
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