Low Rank Affine Adversarial Attacks on Image Classifiers

Aizhan Issagali, Catherine F. Higham, Desmond J. Higham, Francesco Tudisco

Springer INdAM Series, 2026

Neural networks for image classification are vulnerable to adversarial attacks; an imperceptible perturbation to an image can cause a change in classification. Standard attack algorithms use explicit or approximate partial derivative information with respect to the input data. Here, we explore the idea of using a less …

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