Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
5-2009
Abstract
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%.
Discipline
Information Security
Publication
Proceedings of 4th International Conference on Internet and Web Applications and Services, Venice, Italy, 2009 May 24-28
Identifier
10.1109/ICIW.2009.67
City or Country
Venice, Italy
Citation
GUPTA, Payas; RAISSI, Chedy; DRAY, Gerard; PONCELET, Pascal; and BRISSAUD, Johan.
SS-IDS: Statistical Signature based IDS. (2009). Proceedings of 4th International Conference on Internet and Web Applications and Services, Venice, Italy, 2009 May 24-28.
Available at: https://ink.library.smu.edu.sg/sis_research/4196
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/ICIW.2009.67