Quantum adversarial machine learning

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Abstract

This work uncovers the vulnerability aspect for quantum machine learning, by showing that quantum classifiers are vulnerable to adversarial perturbations. The authors give generic recipes on how to generate adversarial perturbations and mitigate the vulnerability problem in various adversarial scenarios.