{"title":"Artificial immune system based intrusion detection","authors":"Eman Abd El Raoof Abas, H. Abdelkader, A. Keshk","doi":"10.1109/INTELCIS.2015.7397274","DOIUrl":null,"url":null,"abstract":"Due to the growing of internet applications, the needs of internet security are increasing. Intrusion detection system is the primary approaches used for saving systems from internal and external intruders. Several techniques have been applied to intrusion detection system such as artificial neural Network, genetic algorithms, artificial immune system. Most researchers suggested improving the intrusion detection performance and accuracy. In this paper, we used artificial immune system network based intrusion detection. In our framework we suggest using GureKddcup database set for intrusion detection and apply R-chunk algorithm of artificial immune system technique, it is used for anomaly detection .An optimized feature selection of rough set theory used for enhancing time consuming.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTELCIS.2015.7397274","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Due to the growing of internet applications, the needs of internet security are increasing. Intrusion detection system is the primary approaches used for saving systems from internal and external intruders. Several techniques have been applied to intrusion detection system such as artificial neural Network, genetic algorithms, artificial immune system. Most researchers suggested improving the intrusion detection performance and accuracy. In this paper, we used artificial immune system network based intrusion detection. In our framework we suggest using GureKddcup database set for intrusion detection and apply R-chunk algorithm of artificial immune system technique, it is used for anomaly detection .An optimized feature selection of rough set theory used for enhancing time consuming.