{"title":"Improved Method for Network Danger Evaluation Based on Immunology Principle","authors":"Jin Yang, Peng Jin, Y. Hong, Gang Luo","doi":"10.1109/ICNC.2009.169","DOIUrl":null,"url":null,"abstract":"This paper proposes an improved immunological surveillance for network danger evaluation model, focusing on intrusion detection and countermeasures with respect to widely-used networks. An improved intrusion detection mechanism based on self-tolerance, clone selection, and immune surveillance is established. A new network security evaluation method using antibody concentration to quantitatively analyze the degree of intrusion danger level is presented. Additionally, this new hierarchical management framework of the proposed model adopt to improve the detection efficiency and to overcome the shortcoming of the local optimum. The experimental results show that the proposed model is a good solution for network security evaluation.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fifth International Conference on Natural Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2009.169","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
This paper proposes an improved immunological surveillance for network danger evaluation model, focusing on intrusion detection and countermeasures with respect to widely-used networks. An improved intrusion detection mechanism based on self-tolerance, clone selection, and immune surveillance is established. A new network security evaluation method using antibody concentration to quantitatively analyze the degree of intrusion danger level is presented. Additionally, this new hierarchical management framework of the proposed model adopt to improve the detection efficiency and to overcome the shortcoming of the local optimum. The experimental results show that the proposed model is a good solution for network security evaluation.