Real-time method for DDoS attacks detection based on self-similarity and wavelet analysis

`rraditional wavelet methods are not efficient to detect the real-time traffic anomaly. To address this drawback, on the basis of self-similarity and wavelet analysis, this paper proposes one real-time method for DDoS attacks detection. Firstly, to effectively analyze new network state, we extracted data packets from network monitor in backward time direction. Secondly, for reducing admissible computing time, we applied time scale self-adjust according to last packets arrival speed. Finally, we adopted three parallel computing strategies to improve real-time performance. Experimental results show that proposed method can quickly and accurately detect DDoS attacks.