The Optimal Application of the Algorithms of Detection and Data Mining in Honeynet

Nanping Dong, Guanling Zhou, Yuping Wang
{"title":"The Optimal Application of the Algorithms of Detection and Data Mining in Honeynet","authors":"Nanping Dong, Guanling Zhou, Yuping Wang","doi":"10.1109/CASE.2009.65","DOIUrl":null,"url":null,"abstract":"This paper puts forward a technical scheme which properly arranges IDS and optimally applies the algorithms of detection and data mining to the Honeynet environment based on a project of building automation system completed by the author recently. In this specific environment, the position of IDS is deployed reasonably and the anomaly and misuse detection algorithm of IDS is designed and selected optimally. Meanwhile, the misuse detection rules are updated dynamically with the combination of data-mining algorithm RIPPER. The design makes the classical and mature algorithms of anomaly detection, misuse detection and RIPPER data mining display their technical characteristics and advantages to the largest extent in the project and enable the honeynet to protect the internal control network as expected.","PeriodicalId":294566,"journal":{"name":"2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CASE.2009.65","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

This paper puts forward a technical scheme which properly arranges IDS and optimally applies the algorithms of detection and data mining to the Honeynet environment based on a project of building automation system completed by the author recently. In this specific environment, the position of IDS is deployed reasonably and the anomaly and misuse detection algorithm of IDS is designed and selected optimally. Meanwhile, the misuse detection rules are updated dynamically with the combination of data-mining algorithm RIPPER. The design makes the classical and mature algorithms of anomaly detection, misuse detection and RIPPER data mining display their technical characteristics and advantages to the largest extent in the project and enable the honeynet to protect the internal control network as expected.
检测和数据挖掘算法在蜜网中的优化应用
本文结合笔者最近完成的一个楼宇自动化系统项目,提出了一种在蜜网环境下合理安排IDS,优化应用检测和数据挖掘算法的技术方案。在此特定环境下,合理部署入侵检测系统的位置,优化设计和选择入侵检测系统的异常和误用检测算法。同时,结合数据挖掘算法RIPPER对误用检测规则进行动态更新。本设计使经典成熟的异常检测、误用检测、RIPPER数据挖掘等算法在项目中最大程度地发挥其技术特点和优势,使蜜网能够如预期的那样保护内控网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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:604180095
Book学术官方微信