{"title":"Modified Ant Miner for Intrusion Detection","authors":"Deven Agravat, Urmi Vaishnav, P. Swadas","doi":"10.1109/ICMLC.2010.52","DOIUrl":null,"url":null,"abstract":"This paper proposes Modified Ant Miner algorithm for intrusion detection. Ant Miner and its descendant have produced good result on many classification problems. Data mining technique is still relatively unexplored area for intrusion detection. In this paper, modification has been suggested in basic ant miner algorithm to improve accuracy and training time of algorithm. The KDD Cup 99 intrusion data set is used to evaluate our proposed algorithm and the result obtained from this experiment is compared with that of Support Vector Machine. It has been found that our proposed algorithm is more effective in case of DOS, U2R, and R2L type of attacks.","PeriodicalId":423912,"journal":{"name":"2010 Second International Conference on Machine Learning and Computing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Machine Learning and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2010.52","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
This paper proposes Modified Ant Miner algorithm for intrusion detection. Ant Miner and its descendant have produced good result on many classification problems. Data mining technique is still relatively unexplored area for intrusion detection. In this paper, modification has been suggested in basic ant miner algorithm to improve accuracy and training time of algorithm. The KDD Cup 99 intrusion data set is used to evaluate our proposed algorithm and the result obtained from this experiment is compared with that of Support Vector Machine. It has been found that our proposed algorithm is more effective in case of DOS, U2R, and R2L type of attacks.
提出了一种改进的蚂蚁挖掘算法用于入侵检测。蚁矿机及其后续算法在许多分类问题上都取得了很好的结果。数据挖掘技术在入侵检测中仍然是一个相对未开发的领域。本文对基本蚂蚁挖掘算法进行了改进，提高了算法的准确率和训练时间。利用KDD Cup 99入侵数据集对该算法进行了验证，并将实验结果与支持向量机的结果进行了比较。实验结果表明，本文提出的算法在DOS、U2R和R2L类型的攻击中更为有效。
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