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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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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anomaly detection
intrusion detection
matching pursuit
network security
signal processing
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description 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.
doi_str_mv 10.26636/jtit.2011.1.1131
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subjects anomaly detection
intrusion detection
matching pursuit
network security
signal processing
title Anomaly Detection Framework Based on Matching Pursuit for Network Security Enhancement
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