The goal of this paper is to prove the potential of fractal analysis techniques in evaluation of network characteristics, especially in detection of anomalies, as a method to reveal self-similarities in generated traffic. After a short review of some anomaly detection methods, one describe in detail a statisticalsignal processing technique based on abrupt change detection.
A case study based on real network data from the database of management variables of a SNMP server demonstrates the power of thesignal processing approach to network anomaly detection