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Mining the Networks of Telecommunication Fraud Groups using Social Network Analysis

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Published:31 July 2017Publication History

ABSTRACT

Telecommunication fraud is one of the most prevalent crimes nowadays, and causes most property loss of victims. The criminals of telecommunication fraud are highly organized, concealed and transnational, making investigators difficult to track and capture the suspects. In this paper, we propose a Telecom Fraud Analysis Model (TFAM) which can unveil the underlying structure of fraud groups and identify the roles of the fraudsters. The links between suspects are built using flight information, and co-offending records. Social network analysis techniques are applied to analyze group structures as well as influences of each member. We collect a real telecom fraud dataset with 113 fraudsters whose fraudulent activities spread across four countries and 17 cities. Experimental results demonstrate that our method can successfully identify the key roles and discover the hidden structure of the fraud groups.

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  1. Mining the Networks of Telecommunication Fraud Groups using Social Network Analysis

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      • Published in

        cover image ACM Conferences
        ASONAM '17: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017
        July 2017
        698 pages
        ISBN:9781450349932
        DOI:10.1145/3110025

        Copyright © 2017 ACM

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        Publication History

        • Published: 31 July 2017

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