{"title":"半自动签名生成的数据挖掘技术","authors":"W. Tylman","doi":"10.1109/DepCoS-RELCOMEX.2009.24","DOIUrl":null,"url":null,"abstract":"This paper presents a novel approach to the task of semi-automatic generation of signatures for misuse-based network intrusion detection. The presented approach is a part of a Basset system, a hybrid misuse-anomaly solution employing Bayesian networks. The signature generation part is intended to work with data received from the Bayesian network, in turn providing the network with signatures for novel attacks.","PeriodicalId":185730,"journal":{"name":"2009 Fourth International Conference on Dependability of Computer Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Data Mining Techniques for Semi-automatic Signature Generation\",\"authors\":\"W. Tylman\",\"doi\":\"10.1109/DepCoS-RELCOMEX.2009.24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a novel approach to the task of semi-automatic generation of signatures for misuse-based network intrusion detection. The presented approach is a part of a Basset system, a hybrid misuse-anomaly solution employing Bayesian networks. The signature generation part is intended to work with data received from the Bayesian network, in turn providing the network with signatures for novel attacks.\",\"PeriodicalId\":185730,\"journal\":{\"name\":\"2009 Fourth International Conference on Dependability of Computer Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Fourth International Conference on Dependability of Computer Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DepCoS-RELCOMEX.2009.24\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fourth International Conference on Dependability of Computer Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DepCoS-RELCOMEX.2009.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data Mining Techniques for Semi-automatic Signature Generation
This paper presents a novel approach to the task of semi-automatic generation of signatures for misuse-based network intrusion detection. The presented approach is a part of a Basset system, a hybrid misuse-anomaly solution employing Bayesian networks. The signature generation part is intended to work with data received from the Bayesian network, in turn providing the network with signatures for novel attacks.