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Erschienen in:
2007 | OriginalPaper | Buchkapitel
A Case-Based Approach to Anomaly Intrusion Detection
verfasst von : Alessandro Micarelli, Giuseppe Sansonetti
Erschienen in: Machine Learning and Data Mining in Pattern Recognition
Verlag: Springer Berlin Heidelberg
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The architecture herein advanced finds its rationale in the visual interpretation of data obtained from monitoring computers and computer networks with the objective of detecting security violations. This new outlook on the problem may offer new and unprecedented techniques for intrusion detection which take advantage of algorithmic tools drawn from the realm of image processing and computer vision. In the system we propose, the normal interaction between users and network configuration is represented in the form of snapshots that refer to a limited number of attack-free instances of different applications. Based on the representations generated in this way, a library is built which is managed according to a case-based approach. The comparison between the query snapshot and those recorded in the system database is performed by computing the Earth Mover’s Distance between the corresponding feature distributions obtained through cluster analysis.