Network Intrusion Detection Using a Stochastic Resonance CFAR Technique

被引：1

作者：

He, Di ^{[1
]}

Leung, Henry ^{[2
]}

机构：

[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China

[2] Univ Calgary, Dept Elect & Comp Engn, Calgary, AB T2N 1N4, Canada

来源：

CIRCUITS SYSTEMS AND SIGNAL PROCESSING | 2009年 / 28卷 / 03期

关键词：

Intrusion detection; Stochastic resonance; Constant false alarm rate; Detection probability; Network traffic; PREDICTION; ATTACKS;

D O I：

10.1007/s00034-008-9087-y

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：

A novel constant false alarm rate (CFAR) intrusion detection method based on stochastic resonance (SR) is proposed in this paper. Using the SR technique improves the spectral power (SP) and the signal-to-noise ratio (SNR) of the network intrusion signal, hence enhancing the detectability of network attacks. The threshold and the detection probability of the proposed SR-CFAR method are derived theoretically. Computer simulations based on standard Defense Advanced Research Projects Agency (DARPA) network intrusion data show that this CFAR method outperforms the linear anomaly intrusion detection methods for various types of intrusions.

引用

页码：361 / 375

页数：15

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