SS-IDS: Statistical Signature based IDS

Security of web servers has become a sensitive subject today. Prediction of normal and abnormal request is problematic due to large number of false alarms in many anomaly based Intrusion, Detection Systems(IDS). SS-IDS derives automatically the parameter profiles from the analyzed data thereby gener...

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Main Authors: GUPTA, Payas, RAISSI, Chedy, DRAY, Gerard, PONCELET, Pascal, BRISSAUD, Johan
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語言:English
出版: Institutional Knowledge at Singapore Management University 2009
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在線閱讀:https://ink.library.smu.edu.sg/sis_research/4196
https://ink.library.smu.edu.sg/context/sis_research/article/5199/viewcontent/ICIW.pdf
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機構: Singapore Management University
語言: English
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總結:Security of web servers has become a sensitive subject today. Prediction of normal and abnormal request is problematic due to large number of false alarms in many anomaly based Intrusion, Detection Systems(IDS). SS-IDS derives automatically the parameter profiles from the analyzed data thereby generating the Statistical Signatures. Statistical Signatures are based on modeling of normal requests and their distribution value without explicit intervention. Several attributes are used to calculate the behavior of the legitimate request on the web server. SS-IDS is best suited for the newly installed web servers which doesn't have low gene number of requests in. the data set to train the IDS and can be used on top of currently used signature based IDS like SNORT. Experiments conducted on real data sets have shown high accuracy up to 99.98% for predicting valid request as valid and false positive rate ranges 3.82-7.84%.