Vulnerability of Quantum-Enhanced Support Vector Machines to Adversarial Attacks and Strategies for Robust Defense

Quantum-enhanced support vector machines (QSVMs) are vulnerable to adversarial attacks, where small perturbations to input data can deceive the classifier. However, simple defense strategies based on data augmentation with crafted adversarial samples can make the QSVM classifier robust against new attacks.