Intrusion detection method for complex network environment based on security situation awareness

Kai Yun; Haosheng Li; Haibo Ma

doi:10.1117/12.2629224

21 April 2022 Intrusion detection method for complex network environment based on security situation awareness

Kai Yun, Haosheng Li, Haibo Ma

Proceedings Volume 12175, International Conference on Network Communication and Information Security (ICNCIS 2021); 121750W (2022) https://doi.org/10.1117/12.2629224
Event: International Conference on Network Communication and Information Security (ICNCIS 2021), 2021, Beijing, China

Abstract

Because the security situation of network environment is affected by many factors, the composition characteristics are relatively complex, resulting in a low rate of intrusion detection. Therefore, a research on intrusion detection method for complex network environment based on security situation awareness is proposed. By constructing the sparse self encoder and improving the penalty factor, the network features under the security situation are extracted under the layer by layer greedy training strategy, the genetic algorithm and ant colony algorithm are integrated to plan the optimal detection path, and the extracted feature results are used as the judgment standard to realize the intrusion detection of the network environment. The test results show that the detection rate of the proposed method for four kinds of intrusion data can reach more than 95%, and the average false positive rate is no more than 1.00%. Obviously, due to the comparison method, it has a good detection effect.

Citation Download Citation

Kai Yun, Haosheng Li, and Haibo Ma "Intrusion detection method for complex network environment based on security situation awareness", Proc. SPIE 12175, International Conference on Network Communication and Information Security (ICNCIS 2021), 121750W (21 April 2022); https://doi.org/10.1117/12.2629224

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