| Generalized federated learning via sharpness aware minimization Z Qu, X Li, R Duan, Y Liu, B Tang, Z Lu International conference on machine learning, 18250-18280, 2022 | 100 | 2022 |
| Context-aware online client selection for hierarchical federated learning Z Qu, R Duan, L Chen, J Xu, Z Lu, Y Liu IEEE Transactions on Parallel and Distributed Systems 33 (12), 4353-4367, 2022 | 58 | 2022 |
| Low-cost influence-limiting defense against adversarial machine learning attacks in cooperative spectrum sensing Z Luo, S Zhao, R Duan, Z Lu, YE Sagduyu, J Xu Proceedings of the 3rd ACM Workshop on Wireless Security and Machine …, 2021 | 11 | 2021 |
| Perception-aware attack: Creating adversarial music via reverse-engineering human perception R Duan, Z Qu, S Zhao, L Ding, Y Liu, Z Lu Proceedings of the 2022 ACM SIGSAC conference on computer and communications …, 2022 | 10 | 2022 |
| How to prevent the poor performance clients for personalized federated learning? Z Qu, X Li, X Han, R Duan, C Shen, L Chen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 8 | 2023 |
| Guessing on Dominant Paths: Understanding the Limitation of Wireless Authentication Using Channel State Information Z Qu, R Duan, X Han, S Zhao, Y Liu, Z Lu 2024 IEEE Symposium on Security and Privacy (SP), 2740-2758, 2024 | 1 | 2024 |
| Understanding the Ineffectiveness of the Transfer Attack in Intrusion Detection System R Duan, W Zhao, ZJ Luo, N Wang, Y Liu, Z Lu Network Security Empowered by Artificial Intelligence, 99-119, 2024 | | 2024 |
| Advancing Adversarial Audio: Human-in-the-Loop Black-Box Attacks R Duan University of South Florida, 2024 | | 2024 |
| Parrot-Trained Adversarial Examples: Pushing the Practicality of Black-Box Audio Attacks against Speaker Recognition Models R Duan, Z Qu, L Ding, Y Liu, Z Lu arXiv preprint arXiv:2311.07780, 2023 | | 2023 |
| Federated Learning for IoT Applications, Attacks and Defense Methods Z Qu, R Duan, Y Liu, Z Lu AI Embedded Assurance for Cyber Systems, 161-181, 2023 | | 2023 |
