Blind Adversarial Pruning: Balance Accuracy, Efficiency and Robustness. - Haidong Xie; Lixin Qian; Xueshuang Xiang; Naijin Liu (CoRR, 2020)

Blind Adversarial Training: Balance Accuracy and Robustness. - Haidong Xie; Xueshuang Xiang; Naijin Liu; Bin Dong (CoRR, 2020)

Blind Adversarial Pruning: Towards The Comprehensive Robust Models With Gradually Pruning Against Blind Adversarial Attacks. - Haidong Xie; Lixin Qian; Xueshuang Xiang; Naijin Liu (ICME, 2021)

Legitimate Adversarial Patches: Evading Human Eyes and Detection Models in the Physical World. - Jia Tan; Nan Ji; Haidong Xie; Xueshuang Xiang (ACM Multimedia, 2021)

Adversarial YOLO: Defense Human Detection Patch Attacks via Detecting Adversarial Patches. - Nan Ji; YanFei Feng; Haidong Xie; Xueshuang Xiang; Naijin Liu (CoRR, 2021)

Adversarial Jamming for a More Effective Constellation Attack. - Haidong Xie; Yizhou Xu; Yuanqing Chen; Nan Ji; Shuai Yuan; Naijin Liu; Xueshuang Xiang (CoRR, 2022)

Low-Interception Waveform: To Prevent the Recognition of Spectrum Waveform Modulation via Adversarial Examples. - Haidong Xie; Jia Tan; Xiaoying Zhang; Nan Ji; Haihua Liao; Zuguo Yu; Xueshuang Xiang; Naijin Liu (CoRR, 2022)

Blind Adversarial Training: Towards Comprehensively Robust Models Against Blind Adversarial Attacks. - Haidong Xie; Xueshuang Xiang; Bin Dong; Naijin Liu (CICAI (2), 2023)

Union label smoothing adversarial training: Recognize small perturbation attacks and reject larger perturbation attacks balanced. - Jinshu Huang; Haidong Xie; Chunlin Wu; Xueshuang Xiang (Future Gener. Comput. Syst., 2023)

Dynamic adversarial jamming-based reinforcement learning for designing constellations. - Yizhou Xu; Haidong Xie; Nan Ji; Yuanqing Chen; Naijin Liu; Xueshuang Xiang (Digit. Commun. Networks, 2024)