2021-2023

📄 How to Prevent the Poor Performance Clients for Personalized Federated Learning?

  Zhe Qu, Xingyu Li, Xiao Han, Rui Duan, Chengchao Shen, and Lixing Chen.

      Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

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📄 Perception-Aware Attack: Creating Adversarial Music via Reverse-Engineering Human Perception

  Rui Duan, Zhe Qu, Shangqing Zhao, Leah Ding, Yao Liu and Zhuo Lu.

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security (CCS), 2022.

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📄 Generalized Federated Learning via Sharpness Aware Minimization

Zhe Qu, Xingyu Li, Rui Duan, Yao Liu, Bo Tang and Zhuo Lu.

Proceedings of the 39th International Conference on Machine Learning (ICML), 2022.

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📄 Context-Aware Online Client Selection for Hierarchical Federated Learning

       Zhe Qu, Rui Duan, Lixing Chen, Jie Xu, Zhuo Lu, Yao Liu.

      Proceedings of the IEEE Transactions on Parallel and Distributed Systems (TPDS)

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📄 Low-cost influence-limiting defense against adversarial machine learning attacks in cooperative spectrum sensing

 Zhengping Luo, Shangqing Zhao, Rui Duan, Zhuo Lu, Yalin E Sagduyu and Jie Xu.

 Proceedings of the ACM Workshop on Wireless Security and Machine Learning (WiseML), 2021

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Bookchapter:

📄 Understanding the Ineffectiveness of the Transfer Attack in Intrusion Detection System

 Rui Duan, Wenwei Zhao, Zhengping Luo, Ning Wang, Yao Liu, and Zhuo Lu.

In Springer Book Series Network Security Enpowered by Artificial Intelligence