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Journal of Zhejiang University SCIENCE C 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/FITEE.2400932


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


Author(s):  Yalu WANG1, Jie LI2, Zhijie HAN3, Pu CHENG3, Roshan KUMAR4

Affiliation(s):  1School of Computer and Information Engineering, Henan University, Kaifeng 475004, China; more

Corresponding email(s):   hanzj@henu.edu.cn

Key Words:  Internet of Things, Network intrusion detection, Spatiotemporal graph neural network, Federated learning, Data privacy.


Yalu WANG1, Jie LI2, Zhijie HAN3, Pu CHENG3, Roshan KUMAR4. FedSTGCN: a novel federated spatiotemporal graph learning-based network intrusion detection for the Internet of Things[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .

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publisher="Zhejiang University Press & Springer",
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Abstract: 
Image generation models have made remarkable progress, and image evaluation is crucial for explaining and driving the development of these models. Previous studies have extensively explored human and automatic evaluations of image generation. Herein, these studies are comprehensively surveyed, specifically for two main parts: evaluation protocols and evaluation methods. First, 10 image generation tasks are summarized by focusing on their differences in evaluation aspects. Based on this, a novel protocol is proposed to cover human and automatic evaluation aspects required for various image generation tasks. Second, the review of automatic evaluation methods in the past five years is highlighted. To our knowledge, this paper presents the first comprehensive summary of human evaluation, encompassing evaluation methods, tools, details, and data analysis methods. Finally, this the challenges and potential directions for image generation evaluation are discussed. We hope that this survey will help researchers to develop a systematic understanding of image generation evaluation, stay updated with the latest advancements in the field, and encourage further research.

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