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Author Alves, Ronnie ♦ Ferreira, Pedro ♦ Belo, O. ♦ Lopes, Joao
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Several Anomalous Situation ♦ Real Data ♦ Fraudulent Behavior ♦ First Method Relies ♦ Valuable Tool ♦ Mining Anomalous Behavior Pattern ♦ Fraud Situation ♦ Small List ♦ Anomaly Detection Method ♦ Telecom Fraud Situation ♦ Superimposed Fraud Detection ♦ Preliminary Result ♦ Dynamic Clustering Analysis ♦ Telecommunication System ♦ Fraud Analyst ♦ Signature Deviation-based Approach ♦ Voice Call Record ♦ Fraud Detection ♦ Entire Week
Description In this paper we tackle the problem of superimposed fraud detection in telecommunication systems. We propose two anomaly detection methods based on the concept of signatures. The first method relies on a signature deviation-based approach while the second on a dynamic clustering analysis. Experiments carried out with real data, voice call records from an entire week, corresponding to approximately 2.5 millions of CDRs and 700 thousand of signatures processed per day, allowed us to detect several anomalous situations. The frauds analysts provide us a small list of 12 customers for whom a fraudulent behavior was detected during this week. Thus, 9 and 11 fraud situations were discovered from each method respectively. Preliminary results and discussion with fraud analysts has already proved that our methods are a valuable tool to assist them in fraud detection. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2006-01-01
Publisher Institution In Proceedings of the DMBA Workshop, on the 12th ACM SIGKDD