Anomaly detection in mobile communication networks using the self-organizing map

Authors:
Rewbenio A. Frota;Guilherme A. Barreto;João C.M. Mota
Affiliations:
Department of Teleinformatics Engineering, Federal University of Ceará (UFC), CP 6005, CEP 60455-760, Fortaleza, Ceará, Brazil;(Correspd. Guilherme@deti.ufc.br) Department of Teleinformatics Engineering, Federal University of Ceará (UFC), CP 6005, CEP 60455-760, Fortaleza, Ceará, Brazil;Department of Teleinformatics Engineering, Federal University of Ceará (UFC), CP 6005, CEP 60455-760, Fortaleza, Ceará, Brazil
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - VIII Brazilian Symposium on Neural Networks
Year:
2007

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Abstract

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.