{"title":"基于模糊随机局部搜索分类器的入侵检测","authors":"B. Bahamida, D. Boughaci","doi":"10.1109/MICAI.2012.17","DOIUrl":null,"url":null,"abstract":"This paper proposes a stochastic local search classifier combined with the fuzzy logic concepts for intrusion detection. The proposed classifier works on knowledge base modeled as a fuzzy rule \"if-then\" and improved by using a stochastic local search. The method is tested on the Benchmark KDD'99 intrusion dataset and compared with other existing techniques for intrusion detection. The results are encouraging and demonstrate the benefit of the proposed approach.","PeriodicalId":348369,"journal":{"name":"2012 11th Mexican International Conference on Artificial Intelligence","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Intrusion Detection Using Fuzzy Stochastic Local Search Classifier\",\"authors\":\"B. Bahamida, D. Boughaci\",\"doi\":\"10.1109/MICAI.2012.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a stochastic local search classifier combined with the fuzzy logic concepts for intrusion detection. The proposed classifier works on knowledge base modeled as a fuzzy rule \\\"if-then\\\" and improved by using a stochastic local search. The method is tested on the Benchmark KDD'99 intrusion dataset and compared with other existing techniques for intrusion detection. The results are encouraging and demonstrate the benefit of the proposed approach.\",\"PeriodicalId\":348369,\"journal\":{\"name\":\"2012 11th Mexican International Conference on Artificial Intelligence\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 11th Mexican International Conference on Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MICAI.2012.17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 11th Mexican International Conference on Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MICAI.2012.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intrusion Detection Using Fuzzy Stochastic Local Search Classifier
This paper proposes a stochastic local search classifier combined with the fuzzy logic concepts for intrusion detection. The proposed classifier works on knowledge base modeled as a fuzzy rule "if-then" and improved by using a stochastic local search. The method is tested on the Benchmark KDD'99 intrusion dataset and compared with other existing techniques for intrusion detection. The results are encouraging and demonstrate the benefit of the proposed approach.
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