Abstract
Due to the frequent occurrence of network security incidents, causing unnecessary losses to people, frequent network security incidents are worrying. For the problems of Internet application network information security, attackers use attacks to continuously threaten them. This paper studies the method of information security monitoring and early warning mechanism for Internet application network based on particle swarm optimization. Based on the support vector regression machine, a network security prediction model with multi-group chaotic particle optimization is established. The prediction results are obtained through the network information security monitoring and early warning mechanism, and the prediction results are analyzed and summarized. The results show that the Internet application network information security prediction model based on particle swarm optimization algorithm can provide guidance for the development of network security solutions and strategies, enhance the initiative of network security defense, reduce the losses caused by network attacks, and have better practicality Sex.
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Acknowledgment
China Southern Power Grid technology project “Information Operation Security System V1.0 product development” (2018030102dx00697).
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Chen, F., Zou, H., Li, Xs. (2020). Research on Information Security Monitoring and Early Warning Mechanism of Internet Application Network Based on Particle Swarm Optimization. In: Zhang, YD., Wang, SH., Liu, S. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 327. Springer, Cham. https://doi.org/10.1007/978-3-030-51103-6_21
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DOI: https://doi.org/10.1007/978-3-030-51103-6_21
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