Fast Network Traffic Anomaly Detection Based on Iteration

As the Internet environment becomes more and more complex and the network scale expands greater and greater, the unexpected anomaly occurs constantly. Due to lag and subjectivity in building a model and the shortage in terms of speed for traditional detection methods, a fast anomaly detection scheme is proposed in this paper, which is based on research into "self-similar" feature. Estimation results show that our scheme has clear advantage in detection speed and accuracy compared with other schemes based on self-similarity.