R. Sarala, G. Zayaraz, V. Vijayalakshmi, R. Sivaranjani
{"title":"Modeling causally dependent events using fuzzy cognitive maps","authors":"R. Sarala, G. Zayaraz, V. Vijayalakshmi, R. Sivaranjani","doi":"10.1109/ICCIC.2014.7238339","DOIUrl":null,"url":null,"abstract":"The increase in the number of security breaches has made information security risk management an essential security activity for all type of organizations. Risk Management involves assessment involves identification of assets, threats and vulnerabilities. Attacks by outsiders continue to cause the most security breaches to all organizations. Existing approaches like attack graph based risk assessment have scalability issues and focus on only single step attacks. It is very difficult to predict multistep attacks that exploit a chain of vulnerabilities. The multistep attacks are based on the causality of relation where every cause has an effect. Causality refers to a cause i.e. one event and consequences i.e. another event that has occurred because of the cause. The proposed system aims to make use of fuzzy cognitive maps to model the causally dependent events. Fuzzy cognitive map is a concrete representation of knowledge that can handle incomplete or conflicting information. This is very important in risk assessment because important information may be unreliable as they may be a result of unreliable measurement techniques. The proposed system will aid in proactive information security risk assessment.","PeriodicalId":187874,"journal":{"name":"2014 IEEE International Conference on Computational Intelligence and Computing Research","volume":"342 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Computational Intelligence and Computing Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIC.2014.7238339","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The increase in the number of security breaches has made information security risk management an essential security activity for all type of organizations. Risk Management involves assessment involves identification of assets, threats and vulnerabilities. Attacks by outsiders continue to cause the most security breaches to all organizations. Existing approaches like attack graph based risk assessment have scalability issues and focus on only single step attacks. It is very difficult to predict multistep attacks that exploit a chain of vulnerabilities. The multistep attacks are based on the causality of relation where every cause has an effect. Causality refers to a cause i.e. one event and consequences i.e. another event that has occurred because of the cause. The proposed system aims to make use of fuzzy cognitive maps to model the causally dependent events. Fuzzy cognitive map is a concrete representation of knowledge that can handle incomplete or conflicting information. This is very important in risk assessment because important information may be unreliable as they may be a result of unreliable measurement techniques. The proposed system will aid in proactive information security risk assessment.