Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning

28 Jul 2020 Jirong Yi Raghu Mudumbai Weiyu Xu

We consider the theoretical problem of designing an optimal adversarial attack on a decision system that maximally degrades the achievable performance of the system as measured by the mutual information between the degraded signal and the label of interest. This problem is motivated by the existence of adversarial examples for machine learning classifiers... (read more)

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