一种高效的基于数据挖掘的入侵检测框架

Weidong Li, Kejun Zhang, Boqun Li, Bingru Yang
{"title":"一种高效的基于数据挖掘的入侵检测框架","authors":"Weidong Li, Kejun Zhang, Boqun Li, Bingru Yang","doi":"10.1109/CIMA.2005.1662306","DOIUrl":null,"url":null,"abstract":"A multi-layer intrusion detection framework is proposed in this paper. Comparing to the traditional system, the framework has sources from all the respects of host computer and network, and calculates connecting volume for each active connection, thus only the suspicious connections would be analyzed, more than 80% packets are normal, and don't need processing, influence to the system speed is very little. All the information of the host computer is combined to a union, and the properties are expanded and enhanced for the data mining engine, so the mining process is efficient and accurate. Fuzzy mining can also be used in intrusion detecting and rule sets comparing. The framework provides abilities of detection, report and response. Experimental results show the rapidness and accuracy of the proposed framework","PeriodicalId":306045,"journal":{"name":"2005 ICSC Congress on Computational Intelligence Methods and Applications","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"An efficient framework for intrusion detection based on data mining\",\"authors\":\"Weidong Li, Kejun Zhang, Boqun Li, Bingru Yang\",\"doi\":\"10.1109/CIMA.2005.1662306\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A multi-layer intrusion detection framework is proposed in this paper. Comparing to the traditional system, the framework has sources from all the respects of host computer and network, and calculates connecting volume for each active connection, thus only the suspicious connections would be analyzed, more than 80% packets are normal, and don't need processing, influence to the system speed is very little. All the information of the host computer is combined to a union, and the properties are expanded and enhanced for the data mining engine, so the mining process is efficient and accurate. Fuzzy mining can also be used in intrusion detecting and rule sets comparing. The framework provides abilities of detection, report and response. Experimental results show the rapidness and accuracy of the proposed framework\",\"PeriodicalId\":306045,\"journal\":{\"name\":\"2005 ICSC Congress on Computational Intelligence Methods and Applications\",\"volume\":\"73 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 ICSC Congress on Computational Intelligence Methods and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIMA.2005.1662306\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 ICSC Congress on Computational Intelligence Methods and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMA.2005.1662306","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

提出了一种多层入侵检测框架。与传统系统相比,该框架从主机和网络的各个方面都有来源,并对每个活动连接计算连接量,因此只分析可疑连接,80%以上的数据包是正常的,不需要处理,对系统速度的影响很小。将主机的所有信息组合成一个union,并对数据挖掘引擎的属性进行扩展和增强,从而提高挖掘过程的效率和准确性。模糊挖掘还可用于入侵检测和规则集比较。该框架提供了检测、报告和响应的能力。实验结果表明了该框架的快速性和准确性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An efficient framework for intrusion detection based on data mining
A multi-layer intrusion detection framework is proposed in this paper. Comparing to the traditional system, the framework has sources from all the respects of host computer and network, and calculates connecting volume for each active connection, thus only the suspicious connections would be analyzed, more than 80% packets are normal, and don't need processing, influence to the system speed is very little. All the information of the host computer is combined to a union, and the properties are expanded and enhanced for the data mining engine, so the mining process is efficient and accurate. Fuzzy mining can also be used in intrusion detecting and rule sets comparing. The framework provides abilities of detection, report and response. Experimental results show the rapidness and accuracy of the proposed framework
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信