On Distinctive Properties of Universal Perturbations
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Abstract (arXiv)
We identify properties of universal adversarial perturbations (UAPs) that distinguish them from standard adversarial perturbations. Specifically, we show that targeted UAPs generated by projected gradient descent exhibit two human-aligned properties: semantic locality and spatial invariance, which standard targeted adversarial perturbations lack. We also demonstrate that UAPs contain significantly less signal for generalization than standard adversarial perturbations -- that is, UAPs leverage non-robust features to a smaller extent than standard adversarial perturbations.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 33 of its 47 references that are in the map. First posted on arXiv 31 Dec 2021.
Builds on
33 of 47 references.
References · 33
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21 more
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Citing papers per year: 2022: 1.
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