Prioritizing disease-causing genes based on network diffusion and rank concordance. - Minghong Fang; Xiaohua Hu 001; Tingting He 003; Yan Wang; Junmin Zhao; Xianjun Shen; Jie Yuan (BIBM, 2014)

A novel disease gene prediction method based on PPI network. - Junmin Zhao; Tingting He 003; Xiaohua Hu 001; Yan Wang; Xianjun Shen; Minghong Fang; Jie Yuan (BIBM, 2014)

Poisoning Attacks to Graph-Based Recommender Systems. - Minghong Fang; Guolei Yang; Neil Zhenqiang Gong; Jia Liu 002 (ACSAC, 2018)

Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach. - Haibo Yang 001; Xin Zhang 054; Minghong Fang; Jia Liu 002 (CDC, 2019)

Toward Low-Cost and Stable Blockchain Networks. - Minghong Fang; Jia Liu 002 (ICC, 2020)

Private and communication-efficient edge learning: a sparse differential gaussian-masking distributed SGD approach. - Xin Zhang 054; Minghong Fang; Jia Liu 002; Zhengyuan Zhu (MobiHoc, 2020)

Adaptive Multi-Hierarchical signSGD for Communication-Efficient Distributed Optimization. - Haibo Yang 001; Xin Zhang 054; Minghong Fang; Jia Liu 002 (SPAWC, 2020)

Local Model Poisoning Attacks to Byzantine-Robust Federated Learning. - Minghong Fang; Xiaoyu Cao; Jinyuan Jia 001; Neil Zhenqiang Gong (USENIX Security Symposium, 2020)

Influence Function based Data Poisoning Attacks to Top-N Recommender Systems. - Minghong Fang; Neil Zhenqiang Gong; Jia Liu 002 (WWW, 2020)

Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning. - Haibo Yang 001; Minghong Fang; Jia Liu 002 (ICLR, 2021)

FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping. - Xiaoyu Cao; Minghong Fang; Jia Liu 002; Neil Zhenqiang Gong (NDSS, 2021)

Data Poisoning Attacks and Defenses to Crowdsourcing Systems. - Minghong Fang; Minghao Sun; Qi Li 012; Neil Zhenqiang Gong; Jin Tian 001; Jia Liu 002 (WWW, 2021)

AFLGuard: Byzantine-robust Asynchronous Federated Learning. - Minghong Fang; Jia Liu 002; Neil Zhenqiang Gong; Elizabeth S. Bentley (ACSAC, 2022)

NET-FLEET: achieving linear convergence speedup for fully decentralized federated learning with heterogeneous data. - Xin Zhang 054; Minghong Fang; Zhuqing Liu; Haibo Yang 001; Jia Liu 002; Zhengyuan Zhu (MobiHoc, 2022)

FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data. - Minghong Fang; Jia Liu 002; Michinari Momma; Yi Sun (SACMAT, 2022)

IPCert: Provably Robust Intellectual Property Protection for Machine Learning. - Zhengyuan Jiang; Minghong Fang; Neil Zhenqiang Gong (ICCV (Workshops), 2023)

Competitive Advantage Attacks to Decentralized Federated Learning. - Yuqi Jia; Minghong Fang; Neil Zhenqiang Gong (CoRR, 2023)

GradSafe: Detecting Jailbreak Prompts for LLMs via Safety-Critical Gradient Analysis. - Yueqi Xie; Minghong Fang; Renjie Pi; Neil Gong 001 (ACL (1), 2024)

Byzantine-Robust Decentralized Federated Learning. - Minghong Fang; Zifan Zhang; Hairi; Prashant Khanduri; Jia Liu 002; Songtao Lu; Yuchen Liu 001; Neil Gong 001 (CCS, 2024)

Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation. - Haibo Yang 001; Peiwen Qiu; Prashant Khanduri; Minghong Fang; Jia Liu 002 (ICML, 2024)

FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error. - Yueqi Xie; Minghong Fang; Neil Zhenqiang Gong (ICML, 2024)

Adversarial Attacks to Multi-Modal Models. - Zhihao Dou; Xin Hu; Haibo Yang 001; Zhuqing Liu; Minghong Fang (LAMPS@CCS, 2024)

Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction. - Zifan Zhang; Minghong Fang; Jiayuan Huang; Yuchen Liu 001 (IFIP Networking, 2024)

On the Hardness of Decentralized Multi-Agent Policy Evaluation Under Byzantine Attacks. - Hairi; Minghong Fang; Zifan Zhang; Alvaro Velasquez; Jia Liu 002 (WiOpt, 2024)

Robust Federated Learning Mitigates Client-side Training Data Distribution Inference Attacks. - Yichang Xu; Ming Yin; Minghong Fang; Neil Zhenqiang Gong (WWW (Companion Volume), 2024)

Poisoning Federated Recommender Systems with Fake Users. - Ming Yin; Yichang Xu; Minghong Fang; Neil Zhenqiang Gong (WWW, 2024)

GradSafe: Detecting Unsafe Prompts for LLMs via Safety-Critical Gradient Analysis. - Yueqi Xie; Minghong Fang; Renjie Pi; Neil Zhenqiang Gong (CoRR, 2024)

PoisonedFL: Model Poisoning Attacks to Federated Learning via Multi-Round Consistency. - Yueqi Xie; Minghong Fang; Neil Zhenqiang Gong (CoRR, 2024)

Tracing Back the Malicious Clients in Poisoning Attacks to Federated Learning. - Yuqi Jia; Minghong Fang; Hongbin Liu 005; Jinghuai Zhang; Neil Zhenqiang Gong (CoRR, 2024)

LoBAM: LoRA-Based Backdoor Attack on Model Merging. - Ming Yin; Jingyang Zhang; Jingwei Sun 002; Minghong Fang; Hai Li 001; Yiran Chen 001 (CoRR, 2024)

Securing Distributed Network Digital Twin Systems Against Model Poisoning Attacks. - Zifan Zhang; Minghong Fang; Mingzhe Chen; Gaolei Li; Xi Lin 003; Yuchen Liu 001 (IEEE Internet Things J., 2024)

Toward Malicious Clients Detection in Federated Learning. - Zhihao Dou; Jiaqi Wang; Wei Sun 013; Zhuqing Liu; Minghong Fang (AsiaCCS, 2025)

Model Poisoning Attacks to Federated Learning via Multi-Round Consistency. - Yueqi Xie; Minghong Fang; Neil Zhenqiang Gong (CVPR, 2025)

A Power Line Backbone-Assisted Wireless Transit Network. - Wei Sun 013; Minghong Fang (ICNP, 2025)

Do We Really Need to Design New Byzantine-robust Aggregation Rules? - Minghong Fang; Seyedsina Nabavirazavi; Zhuqing Liu; Wei Sun 013; Sundaraja Sitharama Iyengar; Haibo Yang 001 (NDSS, 2025)

Byzantine-Robust Federated Learning over Ring-All-Reduce Distributed Computing. - Minghong Fang; Zhuqing Liu; Xuecen Zhao; Jia Liu 002 (WWW (Companion Volume), 2025)

Provably Robust Federated Reinforcement Learning. - Minghong Fang; Xilong Wang; Neil Zhenqiang Gong (WWW, 2025)

Poisoning Attacks and Defenses to Federated Unlearning. - Wenbin Wang; Qiwen Ma; Zifan Zhang; Yuchen Liu 001; Zhuqing Liu; Minghong Fang (WWW (Companion Volume), 2025)

Traceback of Poisoning Attacks to Retrieval-Augmented Generation. - Baolei Zhang; Haoran Xin 002; Minghong Fang; Zhuqing Liu; Biao Yi; Tong Li 011; Zheli Liu (WWW, 2025)

Practical Poisoning Attacks against Retrieval-Augmented Generation. - Baolei Zhang; Yuxi Chen; Minghong Fang; Zhuqing Liu; Lihai Nie; Tong Li 011; Zheli Liu (CoRR, 2025)

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation. - Baolei Zhang; Haoran Xin 002; Jiatong Li; Dongzhe Zhang; Minghong Fang; Zhuqing Liu; Lihai Nie; Zheli Liu (CoRR, 2025)

VReaves: Eavesdropping on Virtual Reality App Identity and Activity via Electromagnetic Side Channels. - Wei Sun 013; Minghong Fang; Mengyuan Li (CoRR, 2025)

Synergizing AI and Digital Twins for Next-Generation Network Optimization, Forecasting, and Security. - Zifan Zhang; Minghong Fang; Dianwei Chen; Xianfeng Yang; Yuchen Liu 001 (IEEE Wirel. Commun., 2025)

Find a Scapegoat: Poisoning Membership Inference Attack and Defense to Federated Learning. - Wenjin Mo; Zhiyuan Li; Minghong Fang; Mingwei Fang (CoRR, 2025)

Enhancing Privacy in Decentralized Min-Max Optimization: A Differentially Private Approach. - Yueyang Quan; Chang Wang; Shengjie Zhai; Minghong Fang; Zhuqing Liu (CoRR, 2025)

On Transferring, Merging, and Splitting Task-Oriented Network Digital Twins. - Zifan Zhang; Minghong Fang; Mingzhe Chen; Yuchen Liu 001 (CoRR, 2025)

Who Taught the Lie? Responsibility Attribution for Poisoned Knowledge in Retrieval-Augmented Generation. - Baolei Zhang; Haoran Xin 002; Yuxi Chen; Zhuqing Liu; Biao Yi; Tong Li 011; Lihai Nie; Zheli Liu; Minghong Fang (CoRR, 2025)

Fairness-Constrained Optimization Attack in Federated Learning. - Harsh Kasyap; Minghong Fang; Zhuqing Liu; Carsten Maple; Somanath Tripathy (CoRR, 2025)

Secure Retrieval-Augmented Generation against Poisoning Attacks. - Zirui Cheng; Jikai Sun; Anjun Gao; Yueyang Quan; Zhuqing Liu; Xiaohua Hu 001; Minghong Fang (CoRR, 2025)