Machine Learning-Based Approach for Identification of SIM Box Bypass Fraud in a Telecom Network Based on CDR Analysis: Case of a Fixed and Mobile Operator in Cameroon-Reference-Cited by-同舟云学术

Machine Learning-Based Approach for Identification of SIM Box Bypass Fraud in a Telecom Network Based on CDR Analysis: Case of a Fixed and Mobile Operator in Cameroon

Published:2023 Issue:02 Volume:11 Page:142-157
ISSN:2327-5219
Container-title:Journal of Computer and Communications
language:
Short-container-title:JCC

Author:

Djomadji Eric Michel Deussom,Basile Kabiena Ivan,Christian Tchapga Tchito,Djoko Ferry Vaneck Kouam,Sone Michael Ekonde

Publisher

Scientific Research Publishing, Inc.

Subject

General Medicine

Reference17 articles.

1. Agence Ecofin (2015) Cameroun: 22,2 milliards FCfa de pertes en 2015 sur les appels téléphoniques frauduleux par Simbox. Agence Ecofin. https://www.agenceecofin.com/gestion-publique/0910-32980-cameroun-22-2-milliards-fcfa-de-pertes-en-2015-sur-les-appels-telephoniques-frauduleux-par-simbox

2. Cameroun: La fraude par simbox peut coûter 18 milliards de F CFA aux opérateurs. JeuneAfrique.https://www.jeuneafrique.com/271158/economie/cameroun-la-fraude-par-simbox-peut-couter-18-milliards-de-f-cfa-aux-operateurs/

3. Revenue Assurance and Fraud: Risque et fraud management (revenue assur-ance).http://risquefraudtelecom.blogspot.com/2012/05/introduction-au-risque-et-fraud.html

4. Karunathilaka, A.V.V.S. (2020) Fraud Detection on International Direct Dial Calls. University of Colombo School of Computing, Colombo.https://dl.ucsc.cmb.ac.lk/jspui/bitstream/123456789/4451/1/2016%20MIT%20029.pdf

5. Reaves, B., Shernan, E., Bates, A., Carter, H. and Traynor, P. (2015) Boxed Out: Blocking Cellular Interconnect Bypass Fraud at the Network Edge. Proceedings of the 24th USENIX Security Symposium, Washington DC, 12-14 August 2015. https://www.usenix.org/system/files/conference/usenixsecurity15/sec15-paper-reaves-boxed.pdf

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