DetectPMFL: Privacy-Preserving Momentum Federated Learning Considering Unreliable Industrial Agents. - Zehui Zhang; Ningxin He; Qingdan Li; Kunshu Wang; Hang Gao 003; Tiegang Gao (IEEE Trans. Ind. Informatics, 2022)

Efficient Privacy-Preserving Federated Deep Learning for Network Intrusion of Industrial IoT. - Ningxin He; Zehui Zhang; Xiaotian Wang; Tiegang Gao (Int. J. Intell. Syst., 2023)

Sea-YOLOv5s: A UAV image-based model for detecting objects in SeaDronesSee dataset. - Xiaotian Wang; Zhongjie Pan; Ningxin He; Tiegang Gao (J. Intell. Fuzzy Syst., 2023)

SVeriFL: Successive verifiable federated learning with privacy-preserving. - Hang Gao 003; Ningxin He; Tiegang Gao (Inf. Sci., 2023)

An efficient model for real-time wildfire detection in complex scenarios based on multi-head attention mechanism. - Xiaotian Wang; Zhongjie Pan; Hang Gao 003; Ningxin He; Tiegang Gao (J. Real Time Image Process., 2023)

Re_useVFL: Reuse of Parameters-Based Verifiable Federated Learning With Privacy Preservation Using Gradient Sparsification. - Ningxin He; Tiegang Gao; Chuan Zhou (IEEE J. Emerg. Sel. Topics Circuits Syst., 2024)

SDASS: secure data auditing for sharing matrix based secret share cloud storage supporting data dynamics. - Gaopeng Zheng; Hang Gao 003; Ningxin He; Tiegang Gao (J. King Saud Univ. Comput. Inf. Sci., 2025)

Cross-Modal Federated Learning among Unimodal Devices. - Yongheng Deng; Ningxin He; Xinyi Li; Fan Wu 014; Yaoxue Zhang; Ju Ren 001 (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2025)