Vulnerability Analysis Method of Network Routing Mechanism based on Knowledge Graph Vulnerability Analysis and Reinforcement Verification Mechanism of Network Routing Mechanism based on Knowledge Graph

被引:0
作者
Zhang, Yu [1 ]
Zhuang, Yi [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Nanjing 210016, Peoples R China
来源
PROCEEDINGS OF 2024 3RD INTERNATIONAL CONFERENCE ON CYBER SECURITY, ARTIFICIAL INTELLIGENCE AND DIGITAL ECONOMY, CSAIDE 2024 | 2024年
基金
中国国家自然科学基金;
关键词
Knowledge Graph; Routing Mechanism; Network Vulnerability Analysis; GCN; Redundant Reinforcement;
D O I
10.1145/3672919.3672927
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Aiming at the influence of space high-energy particle radiation on the reliability and security of space-based network communication mechanism, we studies the routing mechanism of space-based network, and proposes a vulnerability analysis method of network routing mechanism based on knowledge graph. Based on the constructed vulnerability knowledge graph of space-based network routing mechanism, combined with graph convolutional neural network and label propagation algorithm, we proposes KGCNLP model, which can make better use of the feature advantages of knowledge graph and has the advantages of high integrity and accuracy. In addition, based on the experimental results of the KGCNLP model, we proposes a redundant reinforcement method to realize the reinforcement of the vulnerability of the network routing mechanism. The experimental results show that the method of fault injection experiment, network routing mechanism vulnerability analysis model construction and redundancy reinforcement proposed in this paper is comprehensive and in-depth. The method of combining knowledge graph with graph convolutional neural network provides a novel and effective way to solve the reliability and security problems of space-based network communication mechanism.
引用
收藏
页码:39 / 43
页数:5
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