- 期刊
Wavelet-based Real Time Detection of Network Traffic Anomalies
並列摘要
Real time network monitoring for intrusions is offered by various host and network based intrusion detection systems. These systems largely use signature or pattern matching techniques at the core and thus are ineffective in detecting unknown anomalous activities. In this paper, we apply signal processing techniques in intrusion detection systems, and develop and implement a framework, called Waveman, for real time wavelet-based analysis of network traffic anomalies. Then, we use two metrics, namely percentage deviation and entropy, to evaluate the performance of various wavelet functions on detecting different types of anomalies like Denial of Service (DoS) attacks and portscans. Our evaluation results show that Coiflet and Paul wavelets perform better than other wavelets in detecting most anomalies considered in this work.
延伸閱讀
- Yeh, C. Y. (2004). Identification of Radar Transmitter Using Wavelet Transform and Neural Network [master's thesis, Yuan Ze University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0009-0112200611325115
- Zhang, W. J., & Liu, Z. J. (2014). Real-Time Ship Motion Prediction Based on Time Delay Wavelet Neural Network. Journal of Applied Mathematics, 2014(), 925-931-083. https://doi.org/10.1155/2014/176297
- Salih, D. M., Noor, S. B. M., HamiruceMerhaban, M., & Kamil, R. (2015). Wavelet Network: Online Sequential Extreme Learning Machine for Nonlinear Dynamic Systems Identification. Advances in Artificial Intelligence, 2015(), a1-10. https://doi.org/10.1155/2015/184318
- Yang, H. H., & Hsu, P. H. (2008). Wavelet Networks for Hyperpsectral Image Classification. 航測及遙測學刊, 13(3), 207-217. https://doi.org/10.6574/JPRS.2008.13(3).5
- 林穎駿（2003）。Applications of Wavelet Transform and Neural Network to Recognize the Power Quality Events〔碩士論文，中原大學〕。華藝線上圖書館。https://doi.org/10.6840/cycu200300663