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Quantum adversarial machine learning
Sirui Lu (Max Planck Institute of Quantum Optics, Tsinghua University), Lu-Ming Duan (Tsinghua University), Dong-Ling Deng (Shanghai Qi Zhi Institute, Tsinghua University)
Physical Review Research
DOI: 10.1103/physrevresearch.2.033212 (Computer Science)
License: CC BY
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.
Published on 06 Aug. 2020