Detecting Network Intrusions Using Signal Processing with Query-Based Sampling Filter

Autor: Jen-Shiang Kouh, Ray-I Chang, Liang-Bin Lai
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: 10.1155/2009/735283
Popis: This paper presents a novel approach for training a network intrusion detection system based on a query-based sampling (QBS) filter. The proposed QBS filter applies the concepts of data quantization to signal processing in order to develop a novel classification system. Through interaction with a partially trained classifier, the QBS filter can use an oracle to produce high-quality training data. We tested the method with a benchmark intrusion dataset to verify its performance and effectiveness. Results show that selecting qualified training data will have an impact not only on the performance but also on overall execution (to reduce distortion). This method can significantly increase the accuracy of the detection rate for suspicious activity and can recognize rare attacks. Additionally, the method can improve the efficiency of real-time intrusion detection models.
Databáze: Directory of Open Access Journals
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