Uncertainty as a Swiss army knife: new adversarial attack and defense ideas based on epistemic uncertainty
Abstract Although state-of-the-art deep neural network models are known to be robust to random perturbations, it was verified that these architectures are indeed quite vulnerable to deliberately crafted perturbations, albeit being quasi-imperceptible. These vulnerabilities make it challenging to dep...
Main Authors: | Omer Faruk Tuna, Ferhat Ozgur Catak, M. Taner Eskil |
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Format: | Article |
Language: | English |
Published: |
Springer
2022-04-01
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Series: | Complex & Intelligent Systems |
Subjects: | |
Online Access: | https://doi.org/10.1007/s40747-022-00701-0 |
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