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Article type: Research Article
Authors: Lei, Fana | Cai, Qiangb | Wei, Guiwua; b; * | Wei, Cunc
Affiliations: [a] School of Mathematical Sciences, Sichuan Normal University, Chengdu, Sichuan, China | [b] School of Business, Sichuan Normal University, Chengdu, Sichuan, China | [c] School of Management, Xihua University, Chengdu, Sichuan, China
Correspondence: [*] Corresponding author: Guiwu Wei, School of Mathematical Sciences, Sichuan Normal University, Chengdu, Sichuan 610101, China. E-mail: weiguiwu@163.com.
Abstract: The increasingly large and complex network brings convenience to our life and production, but it also brings potential dangers. Any minor vulnerability may lead to failure of application software configuration, software maintenance, user management and system management. Eventually, our network is interrupted, and even life and production data are leaked. Therefore, establishing a scientific and effective network security evaluation model is an effective way to supervise, manage and improve network security; It is also an effective measure to reduce the loss of life and production. Therefore, we first selected six factors closely related to network security to form a complete network security evaluation index system. Then, the utility function in the traditional measurement of alternatives and ranking according to compromise solution (MARCOS) method is improved by using the value function in cumulative prospect theory (CPT), and a PDHL-MARCOS evaluation model that can reflect the decision-makers’ (DMs’) attitudes towards gains and losses is obtained in the probabilistic double hierarchy linguistic term set (PDHLTS). In addition, the relative entropy (RE) method is also used to obtain expert weights. The combination weights of attributes are obtained using the correlation coefficient and the standard deviation (CCSD) method and the weight function in CPT.
Keywords: Probabilistic double hierarchy linguistic term set (PDHLTS), cumulative prospect theory (CPT), MARCOS method, network security evaluation model
DOI: 10.3233/KES-230120
Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 28, no. 2, pp. 359-387, 2024
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