POBA-GA: Perturbation Optimized Black-Box Adversarial Attacks via Genetic Algorithm
POBA-GA: Perturbation Optimized Black-Box Adversarial Attacks via Genetic Algorithm
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Ithaca: Cornell University Library, arXiv.org
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English
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Publisher
Ithaca: Cornell University Library, arXiv.org
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Contents
Most deep learning models are easily vulnerable to adversarial attacks. Various adversarial attacks are designed to evaluate the robustness of models and develop defense model. Currently, adversarial attacks are brought up to attack their own target model with their own evaluation metrics. And most of the black-box adversarial attack algorithms can...
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Full title
POBA-GA: Perturbation Optimized Black-Box Adversarial Attacks via Genetic Algorithm
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Author / Creator
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TN_cdi_proquest_journals_2237714405
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2237714405
Other Identifiers
E-ISSN
2331-8422
DOI
10.48550/arxiv.1906.03181
