CallMine: Fraud Detection and Visualization of Million-Scale Call Graphs
Authors: 
Mirela Cazzolato, Saranya Vijayakumar, Meng-Chieh Lee, Catalina Vajiac, Namyong Park, Pedro Fidalgo, Agma J.M. Traina, 
Christos FaloutsosAuthors Info & Claims
Mirela Cazzolato, Saranya Vijayakumar, Meng-Chieh Lee, Catalina Vajiac, Namyong Park, Pedro Fidalgo, Agma J.M. Traina, Christos FaloutsosAuthors Info & ClaimsPages 4509 - 4515
Abstract
Given a million-scale dataset of who-calls-whom data containing imperfect labels, how can we detect existing and new fraud patterns? We propose CallMine, with carefully designed features and visualizations. Our CallMine method has the following properties: (a) Scalable, being linear on the input size, handling about 35 million records in around one hour on a stock laptop; (b) Effective, allowing natural interaction with human analysts; (c) Flexible, being applicable in both supervised and unsupervised settings; (d) Automatic, requiring no user-defined parameters.
In the real world, in a multi-million-scale dataset, CallMine was able to detect fraudsters 7,000x faster, namely in a matter of hours, while expert humans took over 10 months to detect them.
CIKM-ARP Categories: Application; Analytics and machine learning; Data presentation.
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Index Terms
- CallMine: Fraud Detection and Visualization of Million-Scale Call Graphs
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October 2023
5508 pages
ISBN:9798400701245
DOI:10.1145/3583780
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- Frank Hopfgartner,
- Mark Lee,
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- Program Chairs:
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Published: 21 October 2023
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- Air Force Research Laboratory (AFRL), the Office of Naval Research (ONR) and the Army Research Office (ARO)
- Portuguese Foundation for Science and Technology - FCT under CMU Portugal
- Sao Paulo Research Foundation - FAPESP
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior - Brasil (CAPES)
- AIDA project - Adaptive, Intelligent and Distributed Assurance Platform
- National Science Foundation Graduate Research
- Pennsylvania Infrastructure Technology Alliance - PITA award
- European Regional Development Fund - ERDF through the Operational Program for Competitiveness and Internationalisation - COMPETE 2020
- National Council for Scientific and Technological Development (CNPq)
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