A modular architecture for the analysis of HTTP payloads based on multiple classifiers

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Abstract

In this paper we propose an Intrusion Detection System (IDS) for the detection of attacks against a web server. The system analyzes the requests received by a web server, and is based on a two-stages classification algorithm that heavily relies on the MCS paradigm. In the first stage the structure of the HTTP requests is modeled using several ensembles of Hidden Markov Models. Then, the outputs of these ensembles are combined using a one-class classification algorithm. We evaluated the system on several datasets of real traffic and real attacks. Experimental results, and comparisons with state-of.the.art detection systems show the effectiveness of the proposed approach. © 2011 Springer-Verlag.

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APA

Ariu, D., & Giacinto, G. (2011). A modular architecture for the analysis of HTTP payloads based on multiple classifiers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6713 LNCS, pp. 330–339). https://doi.org/10.1007/978-3-642-21557-5_35

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