Design of a Snort-Based Hybrid Intrusion Detection System

Authors:
J. Gómez;C. Gil;N. Padilla;R. Baños;C. Jiménez
Affiliations:
Dpt. Lenguajes y Computación, Universidad de Almería, Spain;Dpt. Arquitectura de Computadores y Electrónica, Universidad de Almería, Spain, Almería, Spain 04120;Dpt. Lenguajes y Computación, Universidad de Almería, Spain;Dpt. Arquitectura de Computadores y Electrónica, Universidad de Almería, Spain, Almería, Spain 04120;Dpt. Lenguajes y Computación, Universidad de Almería, Spain
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Year:
2009

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Abstract

Computer security has become a major problem in our society. In particular, computer network security is concerned with preventing the intrusion of an unauthorized person into a network of computers. An intrusion detection system (IDS) is a tool to monitor the network traffic and users' activity with the aim of distinguishing between hostile and non-hostile traffic. Snort is an IDS available under GPL, which allows pattern search. This paper presents a new anomaly pre-processor that extends the functionality of Snort IDS, making it a hybrid IDS.