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Jun, 2023
深度学习中的分量反向误差攻击
Adversarial Ink: Componentwise Backward Error Attacks on Deep Learning
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Lucas Beerens, Desmond J. Higham
TL;DR
本研究从数值分析的角度出发,提出了一种新的类别攻击算法,并研究了使用分量条件数量化易感性。这种攻击在手写文件或印刷文本中广泛适用,揭示了安全风险。
Abstract
deep neural networks
are capable of state-of-the-art performance in many classification tasks. However, they are known to be vulnerable to
adversarial attacks
-- small perturbations to the input that lead to a ch
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