Anomaly detection in mobile communication networks using the self-organizing map
Rewbenio A. Frota, Guilherme A. Barreto, João Mota · Journal of Intelligent & Fuzzy Systems · 2007
Anomaly detection is a pattern recognition task whose goal is to report the occurrence of abnormal or unknown behavior in a given system being monitored. In this paper we propose a general procedure for the computation of decision thresholds for anomaly detection in mobile communication networks. The proposed method is based on Kohonen's Self-Organizing Map (SOM) and the computation of nonparametric (i.e. percentile-based) confidence intervals. Through simulations we compare the performance of the proposed and standard SOM-based anomaly detection methods with respect to the false positive rates produced.