Study to use NEO4J to Analysis and Detection SIM-BOX Fraud
Abstract
The high price of incoming international calls is a common method of subsidizing telephony infrastructure in the developing world. Accordingly, international tele- phone system interconnections are regulated to ensure call quality and accurate billing. High call tariffs create a strong incentive to evade such interconnects and deliver costly international calls illicitly. Specifically, adversaries use VoIP-GSM gateways, informally known as “simboxes” to receive incoming calls over wired data connections and deliver them into a cellular voice network through a local call that appears to originate from a customer’s phone. In this paper, we analyze and compare known methods of fraud detection (sim-box), explaining the advantages and defects for each method and proposing a new method. System relies on analyze CDR files using data mining technology (Neo4j), and then use the known method TCG (test call generation) to increase efficiency and to be more sure to results.
Full text article
References
[1]-M. Yelland, “Fraud in mobile networks,” Computer Fraud & Security, vol. 2013, no. 3, pp. 5–9, 2013.
[2]-A .Gent, “Fighting fraud on mobile networks”, Computer Fraud & Security,feb2017
[3]-RD GENERATION PARTNERSHIP PROJECT. 3GPP TS 46.010 v11.1.0. Tech. Rep. Full rate speech; Transcoding.
[4]-Tariku, A. (2015). Mining Insurance Data For Fraud Detection: The Case of Africa Insurance Share Company. AAU, Faculty of Informatics,
[5]-Two-Crows. (2006).Introduction to Data Mining and Knowledge Discovery (3rd edition ed.): Two [7]Crows Corporation. Bounsaythip , C., & Rinta-Runsala, E. (2001).
[6]-Overview of data mining forcustomer behavior modeling. VTT Information Technology, 18, 1-53.
[7]-H. Windsor, ”Mobile Revenue Assurance Fraud Management,” Juniper Research, http://goo.gl/GX7G4.
[8]-M. Yelland, ”Fraud in mobile networks,” Computer Fraud & Security, vol. 2013, no. 3, pp. 5-9, 2017.
[9]-”Raids on SIM Box/GSM Gateway Fraudsters Save Mobile Operators Millions,”Reuters, http://goo.gl/pHCpK.
[10]-”Fraud in the Mobile World,” Revector, http://goo.gl/Uobx6. Murynets, M. Zabarankin, R.P. Jover and A. Panagia, ”Analysis and detection of SIMbox fraud in mobility networks,” INFOCOM, 2016Proceedings IEEE, pp. 1519-1526,May 2016.
[11]-H. Elmi, S. Ibrahim, and R. Sallehuddin, ”Detecting sim box fraud using neural network,” in IT Convergence and Security 2012. Springer, 2013, pp. 575-582.
[12]-Risk Management, http://www.zira.com.ba/products/risk-managemet/n2b-fraud-management-system/sim-box.
[13]-G. Kesavaraj, S. Sukumaran, ”A study on classification techniques in data mining,” International Conference on Computing, Communications and Networking Tech-nologies (ICCCNT), pp. 1-7, July 2013.
[14]-T. M. Mitchellz, ”Machine Learning,”,Published by McGraw-Hill, March 2005. 11.
[15]-Y. Freund, ”The alternating decision tree learning algorithm,” in Machine Learning: Proceedings of the Sixteenth International Conference, March 2014.12.
[16]-I. Murynets and R. Piqueras Jover, ”Crime scene investigation: SMS spam data analysis,” in Proceedings of the 2017ACM conference on Internet measurement.
Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
In a brief statement, the rights relate to the publication and distribution of research published in the journal of the University of Sebha where authors who have published their articles in the journal of the university of Sebha should how they can use or distribute their articles. They reserve all their rights to the published works, such as (but not limited to) the following rights:
- Copyright and other property rights related to the article, such as patent rights.
- Research published in the journal of the University of Sebha and used in its future works, including lectures and books, the right to reproduce articles for their own purposes, and the right to self-archive their articles.
- The right to enter a separate article, or for a non-exclusive distribution of their article with an acknowledgment of its initial publication in the journal of Sebha University.
Privacy Statement The names and e-mail addresses entered on the Sabha University Journal site will be used for the aforementioned purposes only and for which they were used.