Research Article
Network Malicious Attack Detection Based on Hierarchical Spatial Attention Mechanism
@INPROCEEDINGS{10.1007/978-3-031-96944-7_13, author={Lihua Jiao and Jianming Liu}, title={Network Malicious Attack Detection Based on Hierarchical Spatial Attention Mechanism}, proceedings={Computer and Information Security. First World Conference, WCCIS 2024, Kuala Lumpur, Malaysia, September 20--22, 2024, Proceedings}, proceedings_a={WCCIS}, year={2026}, month={11}, keywords={Hierarchical Spatial Attention Mechanism Network Security Malicious Attack Detection Deep Learning Feature Extraction}, doi={10.1007/978-3-031-96944-7_13} }- Lihua Jiao
Jianming Liu
Year: 2026
Network Malicious Attack Detection Based on Hierarchical Spatial Attention Mechanism
WCCIS
Springer
DOI: 10.1007/978-3-031-96944-7_13
Abstract
In today’s information age, network malicious attacks have become a serious security issue, posing a significant threat to data integrity, confidentiality, and availability. In order to effectively detect and respond to these attacks, this paper pro-poses a network malicious attack detection method HSAM (Hierarchical Spatial Attention Mechanism) based on a hierarchical spatial attention mechanism. By constructing a deep learning model and integrating a hierarchical spatial attention mechanism, this method can capture the spatiotemporal features of network traffic data, significantly improving the accuracy of malicious attack detection.
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