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FedSTGCN: a novel federated spatiotemporal graph learning-based network intrusion detection method for the Internet of Things
Regular Papers | Updated：2025-07-28

    • FedSTGCN: a novel federated spatiotemporal graph learning-based network intrusion detection method for the Internet of Things

      Enhanced Publication
    • FedSTGCN：一种基于联邦时空图学习的物联网网络入侵检测新方法
    • “In the field of IoT network security, a new model called FedSTGCN has been proposed. This model integrates spatiotemporal graph neural networks and federated learning, enabling collaborative model training across distributed IoT devices without raw data sharing. It improves network intrusion detection accuracy while preserving data privacy.”
    • Frontiers of Information Technology & Electronic Engineering   Vol. 26, Issue 7, Pages: 1164-1179(2025)

    • DOI：10.1631/FITEE.2400932    

      CLC： TP39

    • Received：20 October 2024，

      Revised：2025-03-25，

      Published：2025-07

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  • Yalu WANG, Jie LI, Zhijie HAN, et al. FedSTGCN: a novel federated spatiotemporal graph learning-based network intrusion detection method for the Internet of Things[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(7): 1164-1179. DOI： 10.1631/FITEE.2400932.

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