Network Security Situation Prediction Method Based On Secure Routing Algorithm
At present, under the background of the rapid development of Internet technology, the scale of the network is getting larger and larger, the network-related data is usually massive, the complexity of the network is also increasing and the heterogeneity is getting higher and higher. By modifying the...
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| Vydáno v: | 2023 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC) s. 1 - 5 |
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| Hlavní autor: | |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
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IEEE
04.12.2023
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| Abstract | At present, under the background of the rapid development of Internet technology, the scale of the network is getting larger and larger, the network-related data is usually massive, the complexity of the network is also increasing and the heterogeneity is getting higher and higher. By modifying the packet header of the dynamic source routing protocol, and by sending various packets to spread the location information of the node, the function of positioning service is completed. Among them, the compliance rule management module completes the routing calculation and the flow table entry issuing module, and completes the compliance check of the data flow and the network connection work. Based on this feature, anomaly detection is performed, and finally, the security status of the entire network is obtained by combining different types of security data. The lifelong learning RBF algorithm is used to predict the network security situation of college students, and the absolute error of the prediction is small. |
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| AbstractList | At present, under the background of the rapid development of Internet technology, the scale of the network is getting larger and larger, the network-related data is usually massive, the complexity of the network is also increasing and the heterogeneity is getting higher and higher. By modifying the packet header of the dynamic source routing protocol, and by sending various packets to spread the location information of the node, the function of positioning service is completed. Among them, the compliance rule management module completes the routing calculation and the flow table entry issuing module, and completes the compliance check of the data flow and the network connection work. Based on this feature, anomaly detection is performed, and finally, the security status of the entire network is obtained by combining different types of security data. The lifelong learning RBF algorithm is used to predict the network security situation of college students, and the absolute error of the prediction is small. |
| Author | Xu, Mingcheng |
| Author_xml | – sequence: 1 givenname: Mingcheng surname: Xu fullname: Xu, Mingcheng email: xumingcheng@163.com organization: Zhengzhou normal university,Zhengzhou,China |
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| PublicationTitle | 2023 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC) |
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| SubjectTerms | College Student Network Internet Network security Neural networks Prediction algorithms Predictive models Routing Secure Routing Algorithm Situation Prediction Wireless communication |
| Title | Network Security Situation Prediction Method Based On Secure Routing Algorithm |
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