一种基于Haar小波变换的低速率拒绝服务攻击检测方法

A Low-Rate Denial-of-Service Attack Detection Method Based on Haar Wavelet Analysis

依据LDoS攻击周期性脉冲突发的特点,提出一种基于Haar小波特征提取的低速率拒绝服务攻击检测方法.该方法采用信号处理技术来分析网络流量提取特征指标,通过小波多尺度分析对网络流量综合诊断,较好地缓解了合法用户背景流量对攻击特征提取的干扰.NS-2仿真实验结果表明,该方法检测率高,消耗计算资源少,具有良好的理论研究和实用价值.

The traditional statistical testing based methods have the shortcomings of low efficiency and high false positives. To solve this problem, according to the characteristic of periodicity and short burst in LDoS flows, a detection method against LDoS attacks has been designed and implemented based on feature extraction using wavelet transform. The proposed method extracts five feature indices of LDoS flows through wavelet multi--scale analysis of network traffic. Experiment results show that the method, capable of detecting the LDoS attack, achieves high detection rate with low computation cost, and hence has good practical value.