Privacy-Preserving and Efficient Range Counting in IoT Networks. - Ruiyang Qin; Bowen Deng; Lele Zheng; Xutong Mu (NaNA, 2021)

A Secure and Fair Double Auction Framework for Cloud Virtual Machines. - Ke Cheng 001; Wei Tong 003; Lele Zheng; Jiaxuan Fu; Xutong Mu; Yulong Shen 001 (IEEE Access, 2021)

FedProc: Prototypical contrastive federated learning on non-IID data. - Xutong Mu; Yulong Shen 001; Ke Cheng 001; Xueli Geng; Jiaxuan Fu; Tao Zhang 029; Zhiwei Zhang (Future Gener. Comput. Syst., 2023)

FedADDP: Privacy-Preserving Personalized Federated Learning with Adaptive Dimensional Differential Privacy. - Yangyang Guo; Tao Zhang 029; Xutong Mu; Haoshuo Li; Xuewen Dong; Qi Li 011 (ICA3PP (5), 2024)

FedDMC: Efficient and Robust Federated Learning via Detecting Malicious Clients. - Xutong Mu; Ke Cheng 001; Yulong Shen 001; Xiaoxiao Li; Zhao Chang; Tao Zhang 029; Xindi Ma (IEEE Trans. Dependable Secur. Comput., 2024)

FedPTA: Prior-Based Tensor Approximation for Detecting Malicious Clients in Federated Learning. - Xutong Mu; Ke Cheng 001; Teng Liu; Tao Zhang 029; Xueli Geng; Yulong Shen 001 (IEEE Trans. Inf. Forensics Secur., 2024)

PriFFT: Privacy-preserving Federated Fine-tuning of Large Language Models via Function Secret Sharing. - Zhichao You; Xuewen Dong; Ke Cheng 001; Xutong Mu; Jiaxuan Fu; Shiyang Ma; Qiang Qu; Yulong Shen 001 (CoRR, 2025)