Network Anomaly Detection Based on Wavelet Analysis

Autor: Ali A. Ghorbani, Wei Lu
Jazyk: angličtina
Rok vydání: 2008
Předmět:
Zdroj: EURASIP Journal on Advances in Signal Processing, Vol 2009 (2008)
Druh dokumentu: article
ISSN: 1687-6172
1687-6180
DOI: 10.1155/2009/837601
Popis: Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.
Databáze: Directory of Open Access Journals
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