An Continuous Wavelet Transform-Based Detection Approach to Traffic Anomalies
Anomalous traffic often has a significant impact on network activities and lead to the severe damage to our networks because they usually are involved with network faults and network attacks. How to detect effectively network traffic anomalies is a challenge for network operators and researchers. This paper proposes a novel method for detecting traffic anomalies in a network, based on continuous wavelet transform. Firstly, continuous wavelet transforms are performed for network traffic in several scales. We then use multi-scale analysis theory to extract traffic characteristics. And these characteristics in different scales are further analyzed and an appropriate detection threshold can be obtained. Consequently, we can make the exact anomaly detection. Simulation results show that our approach is effective and feasible.
Network traffic anomaly detection continuous wavelet transform multi-scale analysis
Dingde Jiang Cheng Yao Zhengzheng Xu Peng Zhang Zhen Yuan Wenda Qin
College of Information Science and Engineering, NEU, Shenyang 110819, China State Key Laboratory of College of Information Science and Engineering, NEU, Shenyang 110819, China
国际会议
合肥
英文
2098-2102
2011-09-23（万方平台首次上网日期，不代表论文的发表时间）