Research on Security Situation Assessment and Prediction Model of Network System in Deep Learning Environment

With the development of the Internet, the network environment is increasingly complex, and the problem of network security is increasingly serious. Traditional passive network security technology has been unable to meet people’s current security needs, in this context, network security situation awareness arises at the historic moment. NSSA technology makes the traditional passive security into active security, from the analysis of unilateral elements to the analysis of the overall security. As key technology of situation perception, security situation assessment and prediction can evaluate and predict the network security situation at the overall level, help network security managers understand the overall network security changes and take protective measures in advance when predicting the dangerous state, which has important research significance. This paper mainly studies the situation assessment and prediction technology of network security, and puts forward the improved model and algorithm, which improves accuracy of situation assessment and prediction results. Prediction accuracy reaches 97.86%, and the efficiency of the situation assessment reaches 98.22%.

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Publication Details

Journal
Journal of Cyber Security and Mobility
Published
2024-11-23
DOI
https://doi.org/10.13052/jcsm2245-1439.1362
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Research on Security Situation Assessment and Prediction Model of Network System in Deep Learning Environment

Yuxian Zhu, Tianheng Pan, Xiaoling Wu, Xiao Li
Journal of Cyber Security and Mobility
Network Security and Intrusion Detection
article

Research on Security Situation Assessment and Prediction Model of Network System in Deep Learning Environment

Yuxian Zhu, Tianheng Pan, Xiaoling Wu, Xiao Li
article en

Abstract

With the development of the Internet, the network environment is increasingly complex, and the problem of network security is increasingly serious. Traditional passive network security technology has been unable to meet people’s current security needs, in this context, network security situation awareness arises at the historic moment. NSSA technology makes the traditional passive security into active security, from the analysis of unilateral elements to the analysis of the overall security. As key technology of situation perception, security situation assessment and prediction can evaluate and predict the network security situation at the overall level, help network security managers understand the overall network security changes and take protective measures in advance when predicting the dangerous state, which has important research significance. This paper mainly studies the situation assessment and prediction technology of network security, and puts forward the improved model and algorithm, which improves accuracy of situation assessment and prediction results. Prediction accuracy reaches 97.86%, and the efficiency of the situation assessment reaches 98.22%.

Journal of Cyber Security and Mobility
Wuhan University (CN), Wuhan Institute of Bioengineering (CN)
Hubei Provincial Department of Education
Peace, Justice and strong institutions
Openalex Percentile: Top 76%
Network Security and Intrusion Detection
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Research on Security Situation Assessment and Prediction Model of Network System in Deep Learning Environment — Yuxian Zhu, Tianheng Pan, et al. · Journal of Cyber Security and Mobility (2024) | TGRS Research Map | TGRS