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A PREVENTION STRATEGY FOR SECURITY: A BAYESIAN APPROACH TO ANOMALIES DETECTION

Conference paper
Part of the IFIP On-Line Library in Computer Science book series (IFIPAICT, volume 177)

Abstract

Intrusion detection is one of the new frontiers in network security, but almost every implemented system is in trouble when it has to deal with new kind of attacks or when it has to give a real time response to predefined attacks. In this work, we assert that the way of improving intrusion detection is to consider the semantic aspects of the communication protocols. Furthermore, we analyze an intrusion detection model that tries to reach this goal putting together database logical design rules and new rules from Bayesian reasoning. In the final section, we sketch some application of the model and we show how to implement the model and how to face existing attacks using the model itself.

Keywords

Mutual Information Bayesian Network Bayesian Approach Intrusion Detection Anomaly Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© International Federation for Information Processing 2005

Authors and Affiliations

  1. 1.Nestor LaboratoryUniversity of Rome“Tor Vergata”Italy

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