Anomaly Detection of Network Traffic Based on Analytical Discrete Wavelet Transform

被引：0

作者：

Salagean, Marius ^{[1
]}

Firoiu, Ioana ^{[1
]}

机构：

[1] Univ Politehn Timisoara, Fac Etc, Dept Commun, Timisoara, Romania

来源：

PROCEEDINGS OF THE 2010 8TH INTERNATIONAL CONFERENCE ON COMMUNICATIONS (COMM) | 2010年

关键词：

network traffic; intrusion detection; signal processing; wavelets; high order statistics; cumulant;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Signal processing techniques have attracted a lot of attention recently in the networking security technology, because of their capability of detecting novel intrusions or attacks. In this paper, we propose a new detection mechanism of network traffic anomaly based on Analytical Discrete Wavelet Transform (ADWT) and high-order statistical analysis. In order to describe the network traffic information, we use a set of features based on different metrics. We evaluate our technique with the 1999 DARPA intrusion detection dataset. The test results show that the proposed approach accurately detects a wide range of anomalies.

引用

页码：49 / 52

页数：4

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