Scam and fraud detection in VoIP Networks: Analysis and countermeasures using user profiling

Theodoros Kapourniotis, George Polyzos, Tasos Dagiuklas, Panagiotis Alefragkis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

This paper presents a VoIP Fraud Detection Framework by exploiting VoIP and/or network-OSS/BSS vulnerabilities. This can be accomplished by analyzing the behavior of the VoIP user using an ontology model so that different types of fraud scenarios could be identified. Using this ontology, an unsupervised learning algorithm has been implemented that describes the user behavior and/or the correlation among various features by analyzing CDR data. The statistical model that has been used is a Bayesian Network. The performance of the proposed model is optimized (minimizing the percentage of false alarms) by configuring the parameters of the Bayesian Network properly.
Original languageEnglish
Title of host publication2011 50th FITCE Congress - "ICT: Bridging an Ever Shifting Digital Divide"
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-5
Number of pages5
ISBN (Electronic)978-1-4577-1210-4
ISBN (Print)978-1-4577-1208-1
DOIs
Publication statusPublished - 19 Jan 2012
Event2011 50th FITCE Congress: "ICT: Bridging an Ever Shifting Digital Divide" - Palermo, Italy
Duration: 31 Aug 20113 Sept 2011

Conference

Conference2011 50th FITCE Congress
Abbreviated titleFITCE
Country/TerritoryItaly
City Palermo
Period31/08/113/09/11

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