Adversarial Attack Defense Method for a Continuous-Variable Quantum Key Distribution System Based on Kernel Robust Manifold Non-Negative Matrix Factorization
Machine learning has been applied in continuous-variable quantum key distribution (CVQKD) systems to address the growing threat of quantum hacking attacks.However, the use of machine learning algorithms for detecting these attacks has uncovered a vulnerability to adversarial disturbances that can compromise security.By subtly perturbing the detecti