{"title":"Dynamic Evolution Systems and Applications in Intrusion Detection Systems","authors":"Xian-Ming Xu, J. Zhan","doi":"10.1109/ISA.2008.82","DOIUrl":null,"url":null,"abstract":"In this paper, we present a dynamic evolution system and build up a model to trace the transition of the system state. This new model differs from the previous methods, such as Bayesian network, artificial neural network, in two aspects: it can adapt the changes of the environment automatically, and it does not need a special training phase to build up a model. Theoretical analysis shows that it is applicable and practical, and furthermore, experimental results show that it has good performance especially in dynamic environment.","PeriodicalId":212375,"journal":{"name":"2008 International Conference on Information Security and Assurance (isa 2008)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Information Security and Assurance (isa 2008)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISA.2008.82","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, we present a dynamic evolution system and build up a model to trace the transition of the system state. This new model differs from the previous methods, such as Bayesian network, artificial neural network, in two aspects: it can adapt the changes of the environment automatically, and it does not need a special training phase to build up a model. Theoretical analysis shows that it is applicable and practical, and furthermore, experimental results show that it has good performance especially in dynamic environment.