{"title":"用灰色关联分析和概率简化中性集改进计算机网络安全评价","authors":"Hong Wang, Gongping Chen*","doi":"10.3233/kes-230103","DOIUrl":null,"url":null,"abstract":"The popularity of computer network has provided great convenience for people’s work and life, but it has also brought corresponding information security problems. It is very important to do a good job in computer network security evaluation. Conventional computer network security evaluation can be realized with the help of firewalls, antivirus software, etc., while in the face of complex computer network applications, it is necessary to adopt a security evaluation method with good operability and wider application range. The computer network security evaluation is viewed as multiple attribute decision-making (MADM) issue. In this paper, an extended probabilistic simplified neutrosophic number grey relational analysis (PSNN-GRA) method is established for computer network security evaluation. The PSNN-GRA method integrated with Criteria Importance Though Intercrieria Correlation (CRITIC) method in probabilistic simplified neutrosophic sets (PSNSs) circumstance is applied to rank the optional alternatives and a numerical example for computer network security evaluation is used to proof the newly proposed method’s practicability along with the comparison with other methods. The results display that the approach is uncomplicated, valid and simple to compute.","PeriodicalId":44076,"journal":{"name":"International Journal of Knowledge-Based and Intelligent Engineering Systems","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving computer network security evaluation with grey relational analysis and probabilistic simplified neutrosophic sets\",\"authors\":\"Hong Wang, Gongping Chen*\",\"doi\":\"10.3233/kes-230103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The popularity of computer network has provided great convenience for people’s work and life, but it has also brought corresponding information security problems. It is very important to do a good job in computer network security evaluation. Conventional computer network security evaluation can be realized with the help of firewalls, antivirus software, etc., while in the face of complex computer network applications, it is necessary to adopt a security evaluation method with good operability and wider application range. The computer network security evaluation is viewed as multiple attribute decision-making (MADM) issue. In this paper, an extended probabilistic simplified neutrosophic number grey relational analysis (PSNN-GRA) method is established for computer network security evaluation. The PSNN-GRA method integrated with Criteria Importance Though Intercrieria Correlation (CRITIC) method in probabilistic simplified neutrosophic sets (PSNSs) circumstance is applied to rank the optional alternatives and a numerical example for computer network security evaluation is used to proof the newly proposed method’s practicability along with the comparison with other methods. The results display that the approach is uncomplicated, valid and simple to compute.\",\"PeriodicalId\":44076,\"journal\":{\"name\":\"International Journal of Knowledge-Based and Intelligent Engineering Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2023-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Knowledge-Based and Intelligent Engineering Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/kes-230103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Knowledge-Based and Intelligent Engineering Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/kes-230103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
摘要
计算机网络的普及为人们的工作和生活提供了极大的便利,但同时也带来了相应的信息安全问题。做好计算机网络安全评估工作非常重要。传统的计算机网络安全评估可以借助防火墙、杀毒软件等来实现,而面对复杂的计算机网络应用,需要采用可操作性好、适用范围更广的安全评估方法。计算机网络安全评价是一个多属性决策问题。本文建立了一种用于计算机网络安全评价的扩展概率简化中性数灰色关联分析(PSNN-GRA)方法。将概率简化中性粒细胞集(PSNSs)环境下的PSNN-GRA方法与criterion Importance - Though intercriteria Correlation (CRITIC)方法相结合,对可选方案进行排序,并以计算机网络安全评价为例,验证了该方法的实用性,并与其他方法进行了比较。结果表明,该方法简单、有效、计算简单。
Improving computer network security evaluation with grey relational analysis and probabilistic simplified neutrosophic sets
The popularity of computer network has provided great convenience for people’s work and life, but it has also brought corresponding information security problems. It is very important to do a good job in computer network security evaluation. Conventional computer network security evaluation can be realized with the help of firewalls, antivirus software, etc., while in the face of complex computer network applications, it is necessary to adopt a security evaluation method with good operability and wider application range. The computer network security evaluation is viewed as multiple attribute decision-making (MADM) issue. In this paper, an extended probabilistic simplified neutrosophic number grey relational analysis (PSNN-GRA) method is established for computer network security evaluation. The PSNN-GRA method integrated with Criteria Importance Though Intercrieria Correlation (CRITIC) method in probabilistic simplified neutrosophic sets (PSNSs) circumstance is applied to rank the optional alternatives and a numerical example for computer network security evaluation is used to proof the newly proposed method’s practicability along with the comparison with other methods. The results display that the approach is uncomplicated, valid and simple to compute.