Adjustable Piecewise Entropy for network traffic anomaly detection
Geng Tian, Zhiliang Wang, Xia Yin, Zimu Li, Xingang Shi, Ziyi Lu, Chao Zhou, Yingya Guo · 2015
Traditional information entropy has been proved to be an effective metric on network traffic anomaly detection. However, such a metric shows some limitations in large scale networks with constantly changing flow numbers, and it makes the traditional entropy inefficient for traffic anomaly detection. To address this problem, we propose Adjustable Piecewise Entropy to improve traditional entropy for traffic anomaly detection.