Cunqian Feng

Adversarial Distillation Defense: A Robust and Lightweight Training Framework for Deep Learning-Based Radar Jamming Recognition

Results indicate that ADD offers an effective strategy for building secure and lightweight deep learning models for radar jamming recognition, and synergistically integrates adversarial training with knowledge distillation to produce lightweight yet robust jamming recognition models.