• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2022, Volume: 15, Issue: 46, Pages: 2562-2569

Original Article

A Fraud Prevention and Secure Cognitive SIM Card Registration Model

Received Date:06 September 2021, Accepted Date:16 September 2022, Published Date:14 December 2022


Background: Most subscriber identification module (SIM) which usually finds their way to mobile phone users are primarily unregistered or pre-registered. Criminals buy these SIM cards, which have fake personal information, activate them and then use them as a channel of attacking vulnerable mobile phone users. Objective: to investigate the existing standards of the registration process, the weakness and how fraudsters leverage the shortcomings of the existing registration to attack unsuspecting subscribers. Methods: The study also proposed an automated theoretical model as an augmented model to ensure the SIM registration process and implementation become secure. Results: In our investigation, we identified that there had been a rise in fraudulent activities in Ghana, and the criminals have adapted to the new trend of committing a crime using mobile phones. The research presented a proposed conceptual model and algorithm for the new SIM registration. The study further conducted a comparative analysis of the principal component adopted to measure the robustness of the registration platform. The criminals mostly use social engineering tactics to trick their victims into disclosing sensitive information or sending money for services yet to be rendered. MNOs request an ID card before registering and activating SIMs, yet criminals can outwit the registration processes and get SIM cards registered through unapproved channels. Conclusion: We found out that the robustness of our model shall prevent SIM pre-registration and unapproved SIM activation due to verification mechanisms in the proposed model. A cognitive learningsystem has automated the registration process that can identify multiple registrations and prevent unapproved activation.

Keywords: SIM Fraud; SIM card; Cognitive System; Mobile Network Operators; Intelligent decisionmaking; SIM Registration


  1. Ameen AO, Akanni OA, Alimi OM, Haliru S. Design and development of a unified subscribers' SIM registration platform using top-down approach. Information Technologist (The). 2016;13(2):91–96.
  2. Lieto A, Radicioni DP. From human to artificial cognition and back: New perspectives on cognitively inspired AI systems. Cognitive Systems Research. 2016;39(16):1–3. Available from: https://doi:10.1016/j.cogsys.2014.11.001
  3. Otu P, S. Enhanced Secure Transaction for Mobile Money Services. Owusu Nyarko-Boateng & Lord Anertei Tetteh. 2020;8(4):1275–1288.
  4. Beck T, Ramrattan R, Pamuk H, Uras BR. 2016.
  5. Nyarko-Boateng O, Kuranchie A, Anning J. The Relevance of E-Library Facility to the Delivery of Education at the High School: An Example from Ghana. International Journal of Scientific & Engineering Research. 2017;8(5):910–918.
  6. Nyarko-Boateng O, Kuranchie A, Anning J. The Relevance of E-Library Facility to the Delivery of Education at the High School: An Example from Ghana. International Journal of Scientific & Engineering Research. 2017;8(5):910–918.
  7. Sumbwanyambe M, Nel A. Assessing the implications of SIM card registration policy in the SADC region. (pp. 1-9) IST-Africa Conference & Exhibition, Nairobi. 2013.
  8. Makoza F. An Exploratory Study on Policy Transfer for SIM Card Registration in Malawi. International Journal of Technology Diffusion. 2015;6(1):33–45. Available from: https://doi.org/10.4018/IJTD.2015010102
  9. Oyediran O, Omoshule A, Misra S, Maskeliūnas R, Damaševičius R. Attitude of mobile telecommunication subscribers towards sim card registration in Lagos State, Southwestern Nigeria. International Journal of System Assurance Engineering and Management. 2019;10(4):783–791. Available from: https://doi.org/10.1007/s13198-019-00809-6
  10. Nyarko-Boateng O, Asante M, Nti IK. Implementation of Advanced Encryption Standard Algorithm with Key Length of 256 Bits for Preventing Data Loss in an Organization. International Journal of Science and Engineering Applications. 2017;6(3).
  11. Oladipo F;, Abdu, Haruna &, Obansa AA. Integrated Subscriber Identification Module Registration. International Journal of Science and Engineering Investigations. 2018;7(75).
  12. Nyarko-Boateng O, Weyori BA, Tetteh LA. Optimized Authentication Model for Online Transaction Payments. Journal of Computer Science. 2020;16(2):225–234.
  13. Nyarko-Boateng O, Adekoya AF, Weyori BA. Investigating QoS and Performance of Received Signal Strength Indicator in Fiber Optics Broadband Data Communication. American Journal of Engineering and Applied Sciences. 2019;12(3):391–401. Available from: https://doi.org/10.3844/ajeassp.2019.391.401
  14. Nti IK, Adakoya AF, Nyarko-Boateng O. A Multifactor Authentication Framework for the National Health Insurance Scheme in Ghana using Machine Learning. American Journal of Engineering and Applied Sciences. 2020;13(4):639–648. Available from: https://doi.org/10.3844/ajeassp.2020.639.648
  15. Nyarko-Boateng O, Adekoya AF, Weyori BA. Adopting Intelligent Modelling to Trace Fault in Underground Optical Network: A Comprehensive Survey. Journal of Computer Science. 2020;16(10):1355–1366. Available from: https://doi:10.3844/jcssp.2020.1355.1366
  16. Martin A, Taylor L. Exclusion and inclusion in identification: regulation, displacement and data justice. Information Technology for Development. 2021;27(1):50–66. Available from: https://doi.org/10.1080/02681102.2020.1811943


© 2022 Boateng et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)


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