Abstract
Intensive development of the communications industry forces operators to pay special attention to fraud control and cybersecurity issues. New technologies allow fraudsters to improve methods of gaining illegal access to transport network infrastructure and it is becoming increasingly difficult for operators to confront this problem. Significant losses from fraud and cybercrime can cause the company to lose part of its revenue and the company can suffer from the decline in investment attractiveness as well as potential brand damage. To avoid this, it is necessary to use specialized technical means that allow timely detection and prevention of illegal actions of attackers. The authors of the article analysed the points of the income loss in providing the IP VPN service within a network of a transport communications operator. A software solution is proposed that performs the tasks of monitoring the correctness of the provision and accounting of access services to a data network using L2VPN/L3VPN technologies or direct connection to an IP/MPLS network.
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References
Bernardo, G.L.: 2018’s Top Telecom Fraud Threats. https://www.thefastmode.com/services-and-innovations/11751-2018-s-top-telecom-fraud-threats
Sahin, M., Francillon, A., Gupta, P., Ahamad, M.: SoK: fraud in telephony networks. In: 2017 IEEE European Symposium on Security and Privacy, pp. 235–250 (2017). https://doi.org/10.1109/eurosp.2017.40
Mark, N., Suren, N.: Network Intventory Reconciliation. Telecom Fraud Management Services Software & Processes, pp. 3–6 (2015). http://www.technology-research.com/products/bizassure/bizassure_toc.php#b14
Baker, D.: Telecom Fraud & Business Assurance Solutions, Services, & Strategies (2019). http://www.technology-research.com/products/fraudmgt.php
McDermott, F., McDermott, J.: ARM Data Center Software’s Cloud-Based Network Inventory Links Network, Operations, Billing, Sales & CRM to One Database (2019). http://bswan.org/single_database_inventory.asp
Knight, P.: Protecting Data from the Insider Threat. Veriato Closes the Security Gap with Massive Data Collection & Machine Learning (2019). http://fraudtech.net/veriato_insider_threat.asp
Jans, M., Lybaert, N., Vanhoof, K.: A framework for internal fraud risk reduction at IT integrating business processes: the IFR2 framework. Int. J. Digit. Account. Res. 9, 1–29 (2009). https://doi.org/10.4192/1577-8517-v9_1
Kim, H., Kwon, W.J.: Multi-line insurance fraud recognition system: a government-led approach in Korea. Risk Manag. Insur. Rev. 92, 131–147 (2006)
Tsung, F., Zhou, Z., Jiang, W.: Applying manufacturing batch techniques to fraud detection with incomplete customer information. IIE Trans. 396, 671–680 (2007)
Hoogs, B., Kiehl, T., Lacomb, C., Senturk, D.: A genetic algorithm approach to detecting temporal patterns indicative of financial statement fraud. Intell. Syst. Account. Finance Manag. 15, 41–56 (2007)
Juszczak, P., Adams, N.M., Hand, D.J., Whitrow, C., Weston, D.J.: Off-the-peg and bespoke classifiers for fraud detection. Comput. Stat. Data Anal. 52(9), 4521–4532 (2008)
Baker, T.: Anti – fraud management survey results, magnify your anti fraud management (2008). http://www.bakertilly.com/cms/public/userfiles/40eb699b88a3fbd294f043905ecdb9b1e448003f/00d16e0290b6ce8f3262342142d8ed8f093ec767Antifraud%20management%20survey_2008.04.pdf
de Reuver, M., Verschuur, E., Nikayin, F., Cerpa, N., Bouwman, H.: Collective action for mobile payment platforms: a case study on collaboration issues between banks and telecom operators. Electron. Commer. Res. Appl. 14(5), 331–344 (2015)
Glick, W.H.: Business Process Reengineering. Wiley Encyclopedia of Management, pp. 1–2 (2015)
Van Vlasselaer, V., Eliassi-Rad, T., Akoglu, L., Snoeck, M., Baesens, B.: Afraid: fraud detection via active inference in time-evolving social networks. In: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 659–666 (2015)
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Radchenko, A., Kolodeznaia, G., Karpovich, I. (2020). Solving the Problem of Income Loss in the Networks of the Transport Telecommunications Operator When Providing the VPN Service. In: Popovic, Z., Manakov, A., Breskich, V. (eds) VIII International Scientific Siberian Transport Forum. TransSiberia 2019. Advances in Intelligent Systems and Computing, vol 1115. Springer, Cham. https://doi.org/10.1007/978-3-030-37916-2_24
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DOI: https://doi.org/10.1007/978-3-030-37916-2_24
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