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Anomaly Detection Framework Based on Matching Pursuit for Network Security Enhancement

In this paper, a framework for recognizing network traffic in order to detect anomalies is proposed. We propose to combine and correlate parameters from different layers in order to detect 0-day attacks and reduce false positives. Moreover, we propose to combine statistical and signal-based features...

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Bibliographic Details
Published in:Journal of Telecommunications and Information Technology 2023-06 (1), p.32-36
Main Authors: Renk, Rafał, Hołubowicz, Witold
Format: Article
Language:English
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Summary:In this paper, a framework for recognizing network traffic in order to detect anomalies is proposed. We propose to combine and correlate parameters from different layers in order to detect 0-day attacks and reduce false positives. Moreover, we propose to combine statistical and signal-based features. The major contribution of this paper are: novel framework for network security based on the correlation approach as well as new signal based algorithm for intrusion detection using matching pursuit.
ISSN:1509-4553
1899-8852
DOI:10.26636/jtit.2011.1.1131