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Data-Free Adversarial Perturbations for Practical Black-Box Attack
Neural networks are vulnerable to adversarial examples, which are malicious inputs crafted to fool pre-trained models. Adversarial examples often exhibit black-box attacking transferability, which allows that adversarial examples crafted for one model can fool another model. However, existing black-...
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| Publicado no: | Advances in Knowledge Discovery and Data Mining |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7206253/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-47436-2_10 |
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