title: A General Framework for Adaptive and Online Detection of Web Attacks creator: Wang, Wei creator: Masseglia, Florent creator: Guyet, Thomas creator: Quiniou, Rene creator: Cordier, Marie-Odile description: Detection of web attacks is an important issue in current defense-in-depth security framework. In this paper, we pro- pose a novel general framework for adaptive and online de- tection of web attacks. The general framework can be based on any online clustering methods. A detection model based on the framework is able to learn online and deal with “con- cept drift” in web audit data streams. Str-DBSCAN that we extended DBSCAN [1] to streaming data as well as StrAP [3] are both used to validate the framework. The detec- tion model based on the framework automatically labels the web audit data and adapts to normal behavior changes while identifies attacks through dynamical clustering of the streaming data. A very large size of real HTTP Log data col- lected in our institute is used to validate the framework and the model. The preliminary testing results demonstrated its effectiveness. date: 2009-04 type: Conference or Workshop Item type: PeerReviewed format: application/pdf identifier: http://www2009.eprints.org/151/1/p1141.pdf identifier: Wang, Wei and Masseglia, Florent and Guyet, Thomas and Quiniou, Rene and Cordier, Marie-Odile (2009) A General Framework for Adaptive and Online Detection of Web Attacks. In: 18th International World Wide Web Conference, April 20th-24th, 2009, Madrid, Spain. relation: http://www2009.eprints.org/151/