A cloud-based approach to network security situational awareness

Yang Jin; Wei Chen; Haosheng Li

doi:10.1117/12.2674700

28 April 2023 A cloud-based approach to network security situational awareness

Yang Jin, Wei Chen, Haosheng Li

Proceedings Volume 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022); 126262K (2023) https://doi.org/10.1117/12.2674700
Event: International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 2022, Zhuhai, China

Abstract

The traditional network security situational awareness method obtains the clustering results of network behavior analysis by using adaptive weight clustering algorithm, which leads to poor perception due to the lack of fusion of situational indicators. In this regard, a cloud computing-based network security situational awareness approach is proposed. By using Hadoop cloud computing network platform to collect security posture information and establish Bayesian network to fuse network security posture indicators and construct a posture perception model. In the experiments, the proposed method is verified for the perception effect. The analysis of the experimental results shows that the proposed method is used for network security situational awareness of network data, and the perception is less time-consuming and has a more excellent performance of network security situational awareness.

Citation Download Citation

Yang Jin, Wei Chen, and Haosheng Li "A cloud-based approach to network security situational awareness", Proc. SPIE 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 126262K (28 April 2023); https://doi.org/10.1117/12.2674700

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