Spatial-Temporal Moving Target Defense: A Markov Stackelberg Game Model H Li, W Shen, Z Zheng International Conference on Autonomous Agents and Multiagent Systems (AAMAS …, 2020 | 21 | 2020 |
Optimal timing of moving target defense: A Stackelberg game model H Li, Z Zheng MILCOM 2019-2019 IEEE Military Communications Conference (MILCOM), 1-6, 2019 | 20 | 2019 |
Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework H Li, X Sun, Z Zheng Advances in Neural Information Processing Systems (NeurIPS), 2022 | 18 | 2022 |
Learning to Backdoor Federated Learning H Li, C Wu, S Zhu, Z Zheng ICLR 2023 Workshop on Backdoor Attacks and Defenses in Machine Learning (BANDS), 2023 | 8 | 2023 |
A First Order Meta Stackelberg Method for Robust Federated Learning Y Pan, T Li, H Li, T Xu, Z Zheng, Q Zhu ICML 2023 Workshop on the 2nd New Frontiers In Adversarial Machine Learning …, 2023 | 5 | 2023 |
Robust moving target defense against unknown attacks: A meta-reinforcement learning approach H Li, Z Zheng International Conference on Decision and Game Theory for Security (GameSec …, 2022 | 5 | 2022 |
Coordinated attacks against federated learning: A multi-agent reinforcement learning approach W Shen, H Li, Z Zheng ICLR 2021 Workshop on Security and Safety in Machine Learning Systems (SecML), 2021 | 3 | 2021 |
A First Order Meta Stackelberg Method for Robust Federated Learning (Technical Report) H Li, T Xu, T Li, Y Pan, Q Zhu, Z Zheng ICML 2023 Workshop on the 2nd New Frontiers In Adversarial Machine Learning …, 2023 | 1 | 2023 |
Learning to Attack Distributionally Robust Federated Learning W Shen, H Li, Z Zheng NeurIPS 2020 Workshop on Scalability, Privacy, and Security in Federated …, 2020 | 1 | 2020 |