Detection of adversarial attacks via disentangling natural images and perturbations

• المؤلفون الرئيسيون: Qing, Yuanyuan, Bai, Tao, Liu, Zhuotao, Moulin, Pierre, Wen, Bihan
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2024
• الموضوعات: Engineering; Adversarial detection; Representation learning
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/178082

The vulnerability of deep neural networks against adversarial attacks, i.e., imperceptible adversarial perturbations can easily give rise to wrong predictions, poses a huge threat to the security of their real-world deployments. In this paper, a novel Adversarial Detection method via Disentangling N...