{"title":"Network awareness of security situation information security measurement method based on data mining","authors":"Jia Wang, Ke Zhang, Jingyuan Li","doi":"10.3233/jifs-233390","DOIUrl":null,"url":null,"abstract":"Awareness of Network Security Situation (abbreviated as NSS for short) technology is in a period of vigorous development recently. NSS technology means network security situational awareness technology. It refers to the technology of collecting, processing, and analyzing various real-time information in the network to understand and evaluate the current network security status. It can not only find network security threats, but also reflect the NSS in the system security metrics, and provide users with targeted security protection measures. Based on data mining methods, this paper analyzed and models perceived threats and security events with data mining algorithms, and improved information security measurement methods based on association analysis. This paper proposed network security information analysis and NSS based on data mining, and analyzed the experimental results of network awareness of NSS information security measurement. The experimental results showed that when the Timer was 8, the accuracy of the awareness of NSS information security measurement method based on data mining can reach 92.89% . The data mining model had the highest accuracy of 93.14% in situation understanding and evaluation of KDDCup-99 dataset. The results showed that the model can accurately predict the NSS. When Timer was 6, the highest accuracy of the model was 92.71% . In general, the NSS prediction mining model based on KDDCup-99 can better understand, evaluate and predict the situation.","PeriodicalId":54795,"journal":{"name":"Journal of Intelligent & Fuzzy Systems","volume":"154 ","pages":"0"},"PeriodicalIF":1.7000,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Intelligent & Fuzzy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/jifs-233390","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Awareness of Network Security Situation (abbreviated as NSS for short) technology is in a period of vigorous development recently. NSS technology means network security situational awareness technology. It refers to the technology of collecting, processing, and analyzing various real-time information in the network to understand and evaluate the current network security status. It can not only find network security threats, but also reflect the NSS in the system security metrics, and provide users with targeted security protection measures. Based on data mining methods, this paper analyzed and models perceived threats and security events with data mining algorithms, and improved information security measurement methods based on association analysis. This paper proposed network security information analysis and NSS based on data mining, and analyzed the experimental results of network awareness of NSS information security measurement. The experimental results showed that when the Timer was 8, the accuracy of the awareness of NSS information security measurement method based on data mining can reach 92.89% . The data mining model had the highest accuracy of 93.14% in situation understanding and evaluation of KDDCup-99 dataset. The results showed that the model can accurately predict the NSS. When Timer was 6, the highest accuracy of the model was 92.71% . In general, the NSS prediction mining model based on KDDCup-99 can better understand, evaluate and predict the situation.
近年来,网络安全态势感知技术(Awareness of Network Security Situation,简称NSS)正处于蓬勃发展的时期。NSS技术是指网络安全态势感知技术。它是指收集、处理和分析网络中各种实时信息,以了解和评估当前网络安全状态的技术。它不仅可以发现网络安全威胁,还可以将NSS反映在系统安全指标中,为用户提供有针对性的安全防护措施。基于数据挖掘方法,利用数据挖掘算法对感知到的威胁和安全事件进行分析和建模,改进了基于关联分析的信息安全度量方法。本文提出了基于数据挖掘的网络安全信息分析和NSS,并分析了网络感知NSS信息安全度量的实验结果。实验结果表明,当Timer为8时,基于数据挖掘的NSS信息安全度量方法的感知准确率可达92.89%。该模型对KDDCup-99数据集的情景理解和评价准确率最高,达到93.14%。结果表明,该模型能较准确地预测NSS。当Timer为6时,模型的最高准确率为92.71%。总的来说,基于KDDCup-99的NSS预测挖掘模型可以更好地理解、评估和预测情况。
期刊介绍:
The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.