Anomaly Detection In Cellular Network Data Using Big Data Analytics
Conference: European Wireless 2014 - 20th European Wireless Conference
05/14/2014 - 05/16/2014 at Barcelona, Spain
Proceedings: European Wireless 2014
Pages: 5Language: englishTyp: PDF
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Authors:
Karatepe, Ilyas Alper (AveaLabs, Turkey)
Zeydan, Engin (AveaLabs & AVEA Communication Services, Turkey)
Abstract:
Anomaly detection is a key component in which perturbations from a normal behavior suggests a misconfigured/ mismatched data in related systems. In this paper, we present a call detail record based anomaly detection method (CADM) that analyzes the users’s calling activities and detects the abnormal behavior of user movements in a real cellular network. CADM is capable of detecting the location of the site that an anomaly has occurred. We evaluate the proposed CADM by performing experiments over the call-detail records of AVEA, a mobile service provider in Turkey.