Embedded network risk model based on random forest algorithm

Yuxiang Ji

doi:10.1117/12.2653215

20 October 2022 Embedded network risk model based on random forest algorithm

Yuxiang Ji

Author Affiliations +

Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 1235029 (2022) https://doi.org/10.1117/12.2653215
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China

Abstract

By extending and optimizing the COSMIC-FFP model, a measurement method for embedded network systems is proposed, which solves the problem that the COSMIC-FFP model does not support the measurement of real-time systems. At the same time, the network fault analysis and the measurement method based on the network scale are designed to improve the accuracy of the network scale. The experimental results show that through the fault analysis and accurate measurement of the embedded network, the proposed method can find out the weak links of risk management in the process of network engineering, realize the real-time measurement of the network system, and reduce the risk of the network engineering process.

Citation Download Citation

Yuxiang Ji "Embedded network risk model based on random forest algorithm", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 1235029 (20 October 2022); https://doi.org/10.1117/12.2653215

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