CRGT-SA: an interlaced and spatiotemporal deep learning model for network intrusion detection
Regular Papers|Updated:2025-07-28
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CRGT-SA: an interlaced and spatiotemporal deep learning model for network intrusion detection
CRGT-SA:基于交错式时空深度学习的网络入侵检测模型
“In the field of cybersecurity, a novel interlaced and spatiotemporal deep learning model called CRGT-SA has been proposed. This model combines CNN with gated TCN and RNN modules to learn spatiotemporal properties and imports the self-attention mechanism to select significant features, providing solutions to protect the Internet from complicated cyberattacks.”
Frontiers of Information Technology & Electronic EngineeringVol. 26, Issue 7, Pages: 1115-1130(2025)
Affiliations:
School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 310027, China
Jue CHEN, Wanxiao LIU, Xihe QIU, et al. CRGT-SA: an interlaced and spatiotemporal deep learning model for network intrusion detection[J]. Frontiers of information technology & electronic engineering, 2025, 26(7): 1115-1130.
DOI:
Jue CHEN, Wanxiao LIU, Xihe QIU, et al. CRGT-SA: an interlaced and spatiotemporal deep learning model for network intrusion detection[J]. Frontiers of information technology & electronic engineering, 2025, 26(7): 1115-1130. DOI: 10.1631/FITEE.2400459.
CRGT-SA: an interlaced and spatiotemporal deep learning model for network intrusion detection