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Disrupting adversarial transferability in deep neural networks
Adversarial attack transferability is well recognized in deep learning. Previous work has partially explained transferability by recognizing common adversarial subspaces and correlations between decision boundaries, but little is known beyond that. We propose that transferability between seemingly d...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122968/ https://www.ncbi.nlm.nih.gov/pubmed/35607626 http://dx.doi.org/10.1016/j.patter.2022.100472 |