Web: http://arxiv.org/abs/2203.07341

Sept. 16, 2022, 1:15 a.m. | Giulio Rossolini, Federico Nesti, Fabio Brau, Alessandro Biondi, Giorgio Buttazzo

cs.CV updates on arXiv.org arxiv.org

This work presents Z-Mask, a robust and effective strategy to improve the
adversarial robustness of convolutional networks against physically-realizable
adversarial attacks. The presented defense relies on specific Z-score analysis
performed on the internal network features to detect and mask the pixels
corresponding to adversarial objects in the input image. To this end, spatially
contiguous activations are examined in shallow and deep layers to suggest
potential adversarial regions. Such proposals are then aggregated through a
multi-thresholding mechanism. The effectiveness of Z-Mask …

analysis arxiv attacks

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