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Issue title: Special Section: Intelligent Data Aggregation Inspired Paradigm and Approaches in IoT Applications
Guest editors: Xiaohui Yuan and Mohamed Elhoseny
Article type: Research Article
Authors: Li, Xinweia; * | Chen, Huib | Ariann, Bryanc
Affiliations: [a] Department Office of Audit, Guilin Medical University of Guangxi, China | [b] Department School of Computer Science and Information Engineering, Guilin University of Electronic Technology, Guilin, China | [c] Department of Human Resources Management, California American University, USA
Correspondence: [*] Corresponding author. Xinwei Li, Department Office of Audit, Guilin Medical University of Guangxi, China. E-mail: lixinwei@glmc.edu.cn.
Abstract: In this paper, the simulation model of computer network security evaluation based on neural network is proposed. Network security has now become one of the focuses of computer communication researchers. Due to the suddenness and human nature of network security problems, it is often difficult to detect problems after they appear. Combined with the characteristics of network security situation prediction problem, the computer network security evaluation model is constructed by BP neural network algorithm, and the network system security detection algorithm is used to evaluate it, to predict the network security posture. Therefore, the defense can be implemented in advance, and the network security belt can be reduced. The resulting hazards will provide constructive advice on the future development of cybersecurity. Through test simulation, the algorithm can be well applied in the simulation model system; it is worth further promotion in practice.
Keywords: neural network, computer network, security evaluation, simulation model
DOI: 10.3233/JIFS-179065
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 71-78, 2019
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