Research Article
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Year 2021, Volume: 5 Issue: 2, 143 - 161, 18.12.2021

Abdulkadir Battal Ruya Samlı

https://doi.org/10.38088/jise.848350

Abstract

References

  • Fukuta, S.F.L. and Nishigaya, T.F.N. (2000). Method and apparatus for determining dynamic flow in a distributed system, EP1120710A2 numbered patent.
  • Alshab, M.A., Bales, P.J., Covington, R.D., Theophilus, J.D. and Trotter, L.M. (2006). Method and system for building, processing, and maintaining scenarios in event-driven information systems, WO2007035452A1 numbered patent.
  • Berg, W.C., McCallum, D.J. and Newman, R.W. (1995). Method and system for managing workflow, US5999911A numbered patent.
  • Randell, J. (1996). Workflow real time intervention, US5826020A numbered patent.
  • Shapiro, M., O'Brien, J.W., Matheson, C.E., Rodriguez, P.R. and Costa, M. (2003). System-wide selective action management, US7290002B2 numbered patent.
  • Kawai, M., Rimoldi, A. and Bassi, G. (2001). Action management support system), US20030233162A1 numbered patent.
  • Akhilomen, J. (2013). Data Mining Application for Cyber Credit-Card Fraud Detection System, Industrial Conference on Data Mining, Advances in Data Mining. Applications and Theoretical Aspects.
  • Mirea, V., Blăjan, A. and Ionescu, L. (2011). Fraud, Corruption And Cyber Crime In A Global Digital Network, Economics, Management, and Financial Markets, 6(2): 373-380.
  • Bignell, K.B. (2006). Authentication in an Internet Banking Environment; Towards Developing a Strategy for Fraud Detection, International Conference on Internet Surveillance and Protection.
  • Dzomira, S. (2014). Electronic Fraud (Cyber Fraud) Risk In The Banking Industry, Zimbabwe, Risk Governance & Control: Financial Markets & Institutions, 4(2): 16-26.
  • Arya, A.S., Ravi, V., Tejasviram, V., Sengupta, N. and Kasabov, N. (2016). Cyber fraud detection using evolving spiking neural network, International Conference on Industrial and Information Systems.
  • Singh, P. and Singh, M. (2015). Fraud Detection by Monitoring Customer Behavior and Activities, International Journal of Computer Applications, 111(11): 23-32.
  • Cai, Y. and Zhu. D. (2016). Fraud detections for online businesses: a perspective from blockchain technology, Financial Innovation, 2.
  • Gupta, P. and Mundra, A. (2015). Online in-auction fraud detection using online hybrid model, International Conference on Computing, Communication & Automation.
  • Ford, V., Siraj, A. and Eberle, W. (2014). Smart grid energy fraud detection using artificial neural networks, IEEE Symposium on Computational Intelligence Applications in Smart Grid.
  • Krenker, A., Volk, M., Sedlar, U., Bešter, J. and Kos, A. (2009). Bidirectional Artificial Neural Networks for Mobile‐Phone Fraud Detection, ETRI Journal, 31(1): 92-94.
  • Olszewski, D. (2014). Fraud detection using self-organizing map visualizing the user profiles, Knowledge-Based Systems, 70: 324-334.
  • Sethi, N., Gera, A. (2014). A Revived Survey of Various Credit Card Fraud Detection Techniques, International Journal of Computer Science and Mobile Computing, 3(4): 780 -791.
  • Rana, P.J. and Baria, J. (2015). A Survey on Fraud Detection Techniques in Ecommerce, International Journal of Computer Applications, 113(14):, 5-7.
  • Abdallah, A., Maarof, M.A. and Zainal, A. (2016). Fraud detection system: A survey, Journal of Network and Computer Applications, 68: 90-113.
  • Arkel, J.H.V., Wagner, J.J., Schweyen, C.L., Mahone, S.M., Tada, D.D., Curtis, T.J. and Hagins, S. (2012). Predictive modeling processes for healthcare fraud detection, US20130006668A1 numbered patent.
  • Arkel, J.H.V., Wagner, J.J., Schweyen, C.L., Mahone, S.M., Tada, D.D., Curtis, T.J. and Hagins, S. (2012). Near real-time healthcare fraud detection, US20130006655A1 numbered patent.
  • Tyler, M., Basant, N., Robin, P. and Rahman, S. (2010). Healthcare insurance claim fraud detection using datasets derived from multiple insurers, US8214232B2 numbered patent.
  • Crawford, S.L., Erickson, C., Miagkikh, V., Steele, M., Thorsen, M. and Tolmanov, S. (2008). Systems and methods for fraud detection via interactive link analysis, S20090044279A1 numbered patent.
  • Turgeman, A., Kedem, O. and Rivner, U. (2015). Method, device, and system of generating fraud-alerts for cyber-attacks, US9552470B2 numbered patent.

An Action Management System Design and Case Study on Its Usage for Cyber Fraud Prevention and Risk Analysis

Year 2021, Volume: 5 Issue: 2, 143 - 161, 18.12.2021

Abdulkadir Battal Ruya Samlı

https://doi.org/10.38088/jise.848350

Abstract

Today, various types of devices are used to be connected to Internet at every moment of the life. This variety of devices present both benefits and problems to individuals and companies. One of the more important problems in cyber world is “fraud detection”. It is known that, malicious uses in the cyber world are increasing rapidly, fraudsters who seek openness in systems cause material and moral damages to both individuals and companies. In the relevant literature, there are many studies on the detection and prevention of cyber frauds in many sectors such as finance, telecommunication and online shopping. This study aims to develop an action management system to detect cyber frauds and follow the actions of the cases with automatic workflows so as to protect the users according to their next actions. It also reveals the results of this action management system’s usage in a case study of a telecommunication company in Turkey.

Keywords

Action management system risk analysis cyber fraud

References

  • Fukuta, S.F.L. and Nishigaya, T.F.N. (2000). Method and apparatus for determining dynamic flow in a distributed system, EP1120710A2 numbered patent.
  • Alshab, M.A., Bales, P.J., Covington, R.D., Theophilus, J.D. and Trotter, L.M. (2006). Method and system for building, processing, and maintaining scenarios in event-driven information systems, WO2007035452A1 numbered patent.
  • Berg, W.C., McCallum, D.J. and Newman, R.W. (1995). Method and system for managing workflow, US5999911A numbered patent.
  • Randell, J. (1996). Workflow real time intervention, US5826020A numbered patent.
  • Shapiro, M., O'Brien, J.W., Matheson, C.E., Rodriguez, P.R. and Costa, M. (2003). System-wide selective action management, US7290002B2 numbered patent.
  • Kawai, M., Rimoldi, A. and Bassi, G. (2001). Action management support system), US20030233162A1 numbered patent.
  • Akhilomen, J. (2013). Data Mining Application for Cyber Credit-Card Fraud Detection System, Industrial Conference on Data Mining, Advances in Data Mining. Applications and Theoretical Aspects.
  • Mirea, V., Blăjan, A. and Ionescu, L. (2011). Fraud, Corruption And Cyber Crime In A Global Digital Network, Economics, Management, and Financial Markets, 6(2): 373-380.
  • Bignell, K.B. (2006). Authentication in an Internet Banking Environment; Towards Developing a Strategy for Fraud Detection, International Conference on Internet Surveillance and Protection.
  • Dzomira, S. (2014). Electronic Fraud (Cyber Fraud) Risk In The Banking Industry, Zimbabwe, Risk Governance & Control: Financial Markets & Institutions, 4(2): 16-26.
  • Arya, A.S., Ravi, V., Tejasviram, V., Sengupta, N. and Kasabov, N. (2016). Cyber fraud detection using evolving spiking neural network, International Conference on Industrial and Information Systems.
  • Singh, P. and Singh, M. (2015). Fraud Detection by Monitoring Customer Behavior and Activities, International Journal of Computer Applications, 111(11): 23-32.
  • Cai, Y. and Zhu. D. (2016). Fraud detections for online businesses: a perspective from blockchain technology, Financial Innovation, 2.
  • Gupta, P. and Mundra, A. (2015). Online in-auction fraud detection using online hybrid model, International Conference on Computing, Communication & Automation.
  • Ford, V., Siraj, A. and Eberle, W. (2014). Smart grid energy fraud detection using artificial neural networks, IEEE Symposium on Computational Intelligence Applications in Smart Grid.
  • Krenker, A., Volk, M., Sedlar, U., Bešter, J. and Kos, A. (2009). Bidirectional Artificial Neural Networks for Mobile‐Phone Fraud Detection, ETRI Journal, 31(1): 92-94.
  • Olszewski, D. (2014). Fraud detection using self-organizing map visualizing the user profiles, Knowledge-Based Systems, 70: 324-334.
  • Sethi, N., Gera, A. (2014). A Revived Survey of Various Credit Card Fraud Detection Techniques, International Journal of Computer Science and Mobile Computing, 3(4): 780 -791.
  • Rana, P.J. and Baria, J. (2015). A Survey on Fraud Detection Techniques in Ecommerce, International Journal of Computer Applications, 113(14):, 5-7.
  • Abdallah, A., Maarof, M.A. and Zainal, A. (2016). Fraud detection system: A survey, Journal of Network and Computer Applications, 68: 90-113.
  • Arkel, J.H.V., Wagner, J.J., Schweyen, C.L., Mahone, S.M., Tada, D.D., Curtis, T.J. and Hagins, S. (2012). Predictive modeling processes for healthcare fraud detection, US20130006668A1 numbered patent.
  • Arkel, J.H.V., Wagner, J.J., Schweyen, C.L., Mahone, S.M., Tada, D.D., Curtis, T.J. and Hagins, S. (2012). Near real-time healthcare fraud detection, US20130006655A1 numbered patent.
  • Tyler, M., Basant, N., Robin, P. and Rahman, S. (2010). Healthcare insurance claim fraud detection using datasets derived from multiple insurers, US8214232B2 numbered patent.
  • Crawford, S.L., Erickson, C., Miagkikh, V., Steele, M., Thorsen, M. and Tolmanov, S. (2008). Systems and methods for fraud detection via interactive link analysis, S20090044279A1 numbered patent.
  • Turgeman, A., Kedem, O. and Rivner, U. (2015). Method, device, and system of generating fraud-alerts for cyber-attacks, US9552470B2 numbered patent.
There are 25 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Abdulkadir Battal 0000-0001-7519-7328

Ruya Samlı 0000-0002-8723-1228

Publication Date December 18, 2021
Published in Issue Year 2021Volume: 5 Issue: 2

Cite

APA Battal, A., & Samlı, R. (2021). An Action Management System Design and Case Study on Its Usage for Cyber Fraud Prevention and Risk Analysis. Journal of Innovative Science and Engineering, 5(2), 143-161. https://doi.org/10.38088/jise.848350
AMA Battal A, Samlı R. An Action Management System Design and Case Study on Its Usage for Cyber Fraud Prevention and Risk Analysis. JISE. December 2021;5(2):143-161. doi:10.38088/jise.848350
Chicago Battal, Abdulkadir, and Ruya Samlı. “An Action Management System Design and Case Study on Its Usage for Cyber Fraud Prevention and Risk Analysis”. Journal of Innovative Science and Engineering 5, no. 2 (December 2021): 143-61. https://doi.org/10.38088/jise.848350.
EndNote Battal A, Samlı R (December 1, 2021) An Action Management System Design and Case Study on Its Usage for Cyber Fraud Prevention and Risk Analysis. Journal of Innovative Science and Engineering 5 2 143–161.
IEEE A. Battal and R. Samlı, “An Action Management System Design and Case Study on Its Usage for Cyber Fraud Prevention and Risk Analysis”, JISE, vol. 5, no. 2, pp. 143–161, 2021, doi: 10.38088/jise.848350.
ISNAD Battal, Abdulkadir - Samlı, Ruya. “An Action Management System Design and Case Study on Its Usage for Cyber Fraud Prevention and Risk Analysis”. Journal of Innovative Science and Engineering 5/2 (December 2021), 143-161. https://doi.org/10.38088/jise.848350.
JAMA Battal A, Samlı R. An Action Management System Design and Case Study on Its Usage for Cyber Fraud Prevention and Risk Analysis. JISE. 2021;5:143–161.
MLA Battal, Abdulkadir and Ruya Samlı. “An Action Management System Design and Case Study on Its Usage for Cyber Fraud Prevention and Risk Analysis”. Journal of Innovative Science and Engineering, vol. 5, no. 2, 2021, pp. 143-61, doi:10.38088/jise.848350.
Vancouver Battal A, Samlı R. An Action Management System Design and Case Study on Its Usage for Cyber Fraud Prevention and Risk Analysis. JISE. 2021;5(2):143-61.
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