A general framework for adaptive and online detection of web attacks

Wei Wang, Florent Masseglia, Thomas Guyet, Rene Quiniou, Marie-Odile Cordier
2009 Proceedings of the 18th international conference on World wide web - WWW '09  
Detection of web attacks is an important issue in current defense-in-depth security framework. In this paper, we propose a novel general framework for adaptive and online detection 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 "concept 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
more » ... to validate the framework. The detection 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 collected in our institute is used to validate the framework and the model. The preliminary testing results demonstrated its effectiveness.
doi:10.1145/1526709.1526897 dblp:conf/www/WangMGQC09 fatcat:5i26nf6sivfwxagxenwrfbmnmm