Research on Model of Assessing Security Situation for Industrial IoT

XiangDong Hu ； ZhaoTao Chen

《International Core Journal of Engineering》 6卷4期 (2020/04) Pp. 80-88

https://doi.org/10.6919/ICJE.202004_6(4).0011

摘要

Aiming at the fact that the current security situation of the Industrial Internet of Things is difficult to be accurately and autonomously perceived and evaluated, an intelligent sensing and assessment model of the Industrial Internet of Things security situation based on particle swarm optimization to optimize the support vector machine is proposed. First, it defines the indicators of industrial IoT security situation assessment, that is, the importance of industrial IoT assets, network vulnerability, and network threats, and proposes calculation formulas for industrial IoT security situation assessment, and combines the methods of gray correlation to obtain security. Situation assessment. Based on this, the particle swarm algorithm is used to optimize the support vector machine to train the security situation assessment model of the Industrial Internet of Things. Moreover, simulation experiments were carried out, and the proposed model was used to evaluate the safety data of the Industrial Internet of Things, and compared with other methods. The results show that the model has the advantages of high prediction accuracy, and has greater advantages than other methods.

關鍵字

Industrial Internet of Things ； Security posture ； Support vector machine ； Particle swarm optimization

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