Fast Network Traffic Anomaly Detection Based on Iteration
Hua Jiang, Liaojun Pang · 2011
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.