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Conference and Workshop Papers
- 2024
[c22]Yueqi Xie, Minghong Fang, Renjie Pi, Neil Gong:
GradSafe: Detecting Jailbreak Prompts for LLMs via Safety-Critical Gradient Analysis. ACL (1) 2024: 507-518- [c21]Haibo Yang, Peiwen Qiu, Prashant Khanduri, Minghong Fang, Jia Liu:
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation. ICML 2024 - [c20]Yueqi Xie, Minghong Fang, Neil Zhenqiang Gong:
FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error. ICML 2024 - [c19]Zifan Zhang, Minghong Fang, Jiayuan Huang, Yuchen Liu:
Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction. IFIP Networking 2024: 423-431 - [c18]Yichang Xu
, Ming Yin, Minghong Fang, Neil Zhenqiang Gong:
Robust Federated Learning Mitigates Client-side Training Data Distribution Inference Attacks. WWW (Companion Volume) 2024: 798-801 - [c17]Ming Yin, Yichang Xu, Minghong Fang, Neil Zhenqiang Gong:
Poisoning Federated Recommender Systems with Fake Users. WWW 2024: 3555-3565 - 2023
- [c16]Zhengyuan Jiang, Minghong Fang, Neil Zhenqiang Gong:
IPCert: Provably Robust Intellectual Property Protection for Machine Learning. ICCV (Workshops) 2023: 3614-3623 - 2022
- [c15]Minghong Fang, Jia Liu, Neil Zhenqiang Gong, Elizabeth S. Bentley:
AFLGuard: Byzantine-robust Asynchronous Federated Learning. ACSAC 2022: 632-646 - [c14]Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, Zhengyuan Zhu:
NET-FLEET: achieving linear convergence speedup for fully decentralized federated learning with heterogeneous data. MobiHoc 2022: 71-80 - [c13]Minghong Fang, Jia Liu, Michinari Momma, Yi Sun:
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data. SACMAT 2022: 173-184 - 2021
- [c12]Haibo Yang, Minghong Fang, Jia Liu:
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning. ICLR 2021 - [c11]Xiaoyu Cao, Minghong Fang, Jia Liu, Neil Zhenqiang Gong:
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping. NDSS 2021 - [c10]Minghong Fang, Minghao Sun, Qi Li, Neil Zhenqiang Gong, Jin Tian, Jia Liu:
Data Poisoning Attacks and Defenses to Crowdsourcing Systems. WWW 2021: 969-980 - 2020
- [c9]Minghong Fang, Jia Liu:
Toward Low-Cost and Stable Blockchain Networks. ICC 2020: 1-6 - [c8]Xin Zhang, Minghong Fang, Jia Liu, Zhengyuan Zhu:
Private and communication-efficient edge learning: a sparse differential gaussian-masking distributed SGD approach. MobiHoc 2020: 261-270 - [c7]Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu:
Adaptive Multi-Hierarchical signSGD for Communication-Efficient Distributed Optimization. SPAWC 2020: 1-5 - [c6]Minghong Fang, Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong:
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning. USENIX Security Symposium 2020: 1605-1622 - [c5]Minghong Fang, Neil Zhenqiang Gong, Jia Liu:
Influence Function based Data Poisoning Attacks to Top-N Recommender Systems. WWW 2020: 3019-3025 - 2019
- [c4]Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu:
Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach. CDC 2019: 5832-5837 - 2018
- [c3]Minghong Fang, Guolei Yang, Neil Zhenqiang Gong, Jia Liu:
Poisoning Attacks to Graph-Based Recommender Systems. ACSAC 2018: 381-392 - 2014
- [c2]Minghong Fang, Xiaohua Hu, Tingting He, Yan Wang, Junmin Zhao, Xianjun Shen, Jie Yuan:
Prioritizing disease-causing genes based on network diffusion and rank concordance. BIBM 2014: 242-247 - [c1]Junmin Zhao, Tingting He, Xiaohua Hu, Yan Wang, Xianjun Shen, Minghong Fang, Jie Yuan:
A novel disease gene prediction method based on PPI network. BIBM 2014: 311-314
Informal and Other Publications
- 2024
- [i24]Ming Yin, Yichang Xu, Minghong Fang, Neil Zhenqiang Gong:
Poisoning Federated Recommender Systems with Fake Users. CoRR abs/2402.11637 (2024) - [i23]Yueqi Xie, Minghong Fang, Renjie Pi, Neil Zhenqiang Gong:
GradSafe: Detecting Unsafe Prompts for LLMs via Safety-Critical Gradient Analysis. CoRR abs/2402.13494 (2024) - [i22]Yichang Xu, Ming Yin, Minghong Fang, Neil Zhenqiang Gong:
Robust Federated Learning Mitigates Client-side Training Data Distribution Inference Attacks. CoRR abs/2403.03149 (2024) - [i21]Zifan Zhang, Minghong Fang, Jiayuan Huang, Yuchen Liu:
Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction. CoRR abs/2404.14389 (2024) - [i20]Yueqi Xie, Minghong Fang, Neil Zhenqiang Gong:
PoisonedFL: Model Poisoning Attacks to Federated Learning via Multi-Round Consistency. CoRR abs/2404.15611 (2024) - [i19]Haibo Yang, Peiwen Qiu, Prashant Khanduri, Minghong Fang, Jia Liu:
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation. CoRR abs/2405.02745 (2024) - [i18]Minghong Fang, Zifan Zhang, Hairi, Prashant Khanduri, Jia Liu, Songtao Lu, Yuchen Liu, Neil Zhenqiang Gong:
Byzantine-Robust Decentralized Federated Learning. CoRR abs/2406.10416 (2024) - [i17]Zifan Zhang, Minghong Fang, Mingzhe Chen, Gaolei Li, Xi Lin, Yuchen Liu:
Securing Distributed Network Digital Twin Systems Against Model Poisoning Attacks. CoRR abs/2407.01917 (2024) - [i16]Yuqi Jia, Minghong Fang, Hongbin Liu, Jinghuai Zhang, Neil Zhenqiang Gong:
Tracing Back the Malicious Clients in Poisoning Attacks to Federated Learning. CoRR abs/2407.07221 (2024) - [i15]Zhihao Dou, Xin Hu, Haibo Yang, Zhuqing Liu, Minghong Fang:
Adversarial Attacks to Multi-Modal Models. CoRR abs/2409.06793 (2024) - [i14]Hairi, Minghong Fang, Zifan Zhang, Alvaro Velasquez, Jia Liu:
On the Hardness of Decentralized Multi-Agent Policy Evaluation under Byzantine Attacks. CoRR abs/2409.12882 (2024) - 2023
- [i13]Yuqi Jia, Minghong Fang, Neil Zhenqiang Gong:
Competitive Advantage Attacks to Decentralized Federated Learning. CoRR abs/2310.13862 (2023) - 2022
- [i12]Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, Zhengyuan Zhu:
NET-FLEET: Achieving Linear Convergence Speedup for Fully Decentralized Federated Learning with Heterogeneous Data. CoRR abs/2208.08490 (2022) - [i11]Minghong Fang, Jia Liu, Neil Zhenqiang Gong, Elizabeth S. Bentley:
AFLGuard: Byzantine-robust Asynchronous Federated Learning. CoRR abs/2212.06325 (2022) - [i10]Minghong Fang, Jia Liu, Michinari Momma, Yi Sun:
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data. CoRR abs/2212.06750 (2022) - 2021
- [i9]Haibo Yang, Minghong Fang, Jia Liu:
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning. CoRR abs/2101.11203 (2021) - [i8]Minghong Fang, Minghao Sun, Qi Li, Neil Zhenqiang Gong, Jin Tian, Jia Liu:
Data Poisoning Attacks and Defenses to Crowdsourcing Systems. CoRR abs/2102.09171 (2021) - 2020
- [i7]Xin Zhang, Minghong Fang, Jia Liu, Zhengyuan Zhu:
Private and Communication-Efficient Edge Learning: A Sparse Differential Gaussian-Masking Distributed SGD Approach. CoRR abs/2001.03836 (2020) - [i6]Minghong Fang, Neil Zhenqiang Gong, Jia Liu:
Influence Function based Data Poisoning Attacks to Top-N Recommender Systems. CoRR abs/2002.08025 (2020) - [i5]Minghong Fang, Jia Liu:
Toward Low-Cost and Stable Blockchain Networks. CoRR abs/2002.08027 (2020) - [i4]Xiaoyu Cao, Minghong Fang, Jia Liu, Neil Zhenqiang Gong:
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping. CoRR abs/2012.13995 (2020) - 2019
- [i3]Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu:
Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach. CoRR abs/1909.04532 (2019) - [i2]Minghong Fang, Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong:
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning. CoRR abs/1911.11815 (2019) - 2018
- [i1]Minghong Fang, Guolei Yang, Neil Zhenqiang Gong, Jia Liu:
Poisoning Attacks to Graph-Based Recommender Systems. CoRR abs/1809.04127 (2018)
Coauthor Index
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