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Review the Recent Fraud Detection Systems for Accounting Area using Blockchain Technology

  • Rania Alsulami (Faculty of Business Administration, University of Tabuk) ;
  • Raghad Albalawi (Faculty of Business Administration, University of Tabuk) ;
  • Manal Albalawi (Faculty of Business Administration, University of Tabuk) ;
  • Hetaf Alsugair (Faculty of Business Administration, University of Tabuk) ;
  • Khaled A. Alblowi (Faculty of Business Administration, University of Tabuk) ;
  • Adel R. Alharbi (College of Computing & Information Technology, University of Tabuk)
  • Received : 2023.05.05
  • Published : 2023.05.30

Abstract

With the increasing interest in blockchain technology and its employment in diverse sectors and industries, including: finance, business, voting, industrial and many other medical and educational applications. Recently, the blockchain technology has played significant role in preventing fraud transactions in accounting systems, as the blockchain offers high security measurements, reduces the need for centralized processing, and blocks access to the organization information and system. Therefore, this paper studies, analyses, and investigates the adoption of blockchain technology with accounting systems, through analyzing the results of several research works which have employed the blockchain technology to secure their accounting systems. In addition, we investigate the performance of applying the deep learning and machine learning approaches for the purpose of fraud detection and classification. As a result of this study, the adoption of blockchain technology will enhance the safety and security of accounting systems, through identifying and classifying the possible frauds that may attack the accounting and business organizations.

Keywords

References

  1. Nugraheni, B.L.Y., Cummings, L.S. and Kilgore, A., 2022. The localised accounting environment in the implementation of fair value accounting in Indonesia. Qualitative Research in Accounting & Management.
  2. Tarmidi, M., Rashid, A.A. and Abdullah, W.M.T.W., 2017. An analysis of computerized accounting system security threats in Malaysian public listed companies. Terengganu International Finance and Economics Journal (TIFEJ), 2(1), pp.28-35.
  3. Feng, Q., He, D., Zeadally, S., Khan, M.K. and Kumar, N., 2019. A survey on privacy protection in blockchain system. Journal of Network and Computer Applications, 126, pp.45-58. https://doi.org/10.1016/j.jnca.2018.10.020
  4. Biktimirov, M.R., Domashev, A.V., Cherkashin, P.A. and Shcherbakov, A.Y., 2017. Blockchain technology: universal structure and requirements. Automatic Documentation and Mathematical Linguistics, 51, pp.235-238. https://doi.org/10.3103/S0005105517060036
  5. Dutta, P., Choi, T.M., Somani, S. and Butala, R., 2020. Blockchain technology in supply chain operations: Applications, challenges and research opportunities. Transportation research part e: Logistics and transportation review, 142, p.102067.
  6. Ali, O., Jaradat, A., Kulakli, A. and Abuhalimeh, A., 2021. A challenges and functionalities. Ieee Access, 9, pp.12730-12749. https://doi.org/10.1109/ACCESS.2021.3050241
  7. Yu, T., Lin, Z. and Tang, Q., 2018. Blockchain: The introduction and its application in financial accounting. Journal of Corporate Accounting & Finance, 29(4), pp.37-47. https://doi.org/10.1002/jcaf.22365
  8. Zheng, Z., Xie, S., Dai, H.N., Chen, X. and Wang, H., 2018. Blockchain challenges and opportunities: A survey. International journal of web and grid services, 14(4), pp.352-375. https://doi.org/10.1504/IJWGS.2018.095647
  9. Liu, M., Wu, K. and Xu, J.J., 2019. How will blockchain technology impact auditing and accounting: Permissionless versus permissioned blockchain. Current Issues in auditing, 13(2), pp.A19-A29. https://doi.org/10.2308/ciia-52540
  10. Dai, J. and Vasarhelyi, M.A., 2017. Toward blockchain-based accounting and assurance. Journal of information systems, 31(3), pp.5-21. https://doi.org/10.2308/isys-51804
  11. Kwilinski, A., 2019. Implementation of blockchain technology in accounting sphere. Academy of Accounting and Financial Studies Journal, 23, pp.1-6.
  12. Zhang, K. and Jacobsen, H.A., 2018. Towards Dependable, Scalable, and Pervasive Distributed Ledgers with Blockchains (Technical Report).
  13. Hassan, M.U., Rehmani, M.H. and Chen, J., 2022. Anomaly detection in blockchain networks: A comprehensive survey. IEEE Communications Surveys & Tutorials.
  14. Kim, J., Nakashima, M., Fan, W., Wuthier, S., Zhou, X., Kim, I. and Chang, S.Y., 2021, May. Anomaly detection based on traffic monitoring for secure blockchain networking. In 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC) (pp. 1-9). IEEE.
  15. Rabieinejad, E., Yazdinejad, A. and Parizi, R.M., 2021, October. A deep learning model for threat hunting in ethereum blockchain. In 2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) (pp. 1185-1190). IEEE.
  16. Vujicic, D., Jagodic, D. and Randic, S., 2018, March. Blockchain technology, bitcoin, and Ethereum: A brief overview. In 2018 17th international symposium infoteh-jahorina (infoteh) (pp. 1-6). IEEE.
  17. Baek, H., Oh, J., Kim, C.Y. and Lee, K., 2019, July. A model for detecting cryptocurrency transactions with discernible purpose. In 2019 Eleventh International Conference on Ubiquitous and Future Networks (ICUFN) (pp. 713-717). IEEE.
  18. Ashfaq, T., Khalid, R., Yahaya, A.S., Aslam, S., Azar, A.T., Alsafari, S. and Hameed, I.A., 2022. A Machine Learning and Blockchain Based Efficient Fraud Detection Mechanism. Sensors, 22(19), p.7162.
  19. Ibrahim, R.F., Elian, A.M. and Ababneh, M., 2021, July. Illicit account detection in the ethereum blockchain using machine learning. In 2021 International Conference on Information Technology (ICIT) (pp. 488-493). IEEE.
  20. Kumar, N., Singh, A., Handa, A. and Shukla, S.K., 2020. Detecting malicious accounts on the Ethereum blockchain with supervised learning. In Cyber Security Cryptography and Machine Learning: Fourth International Symposium, CSCML 2020, Be'er Sheva, Israel, July 2-3, 2020, Proceedings 4 (pp. 94-109). Springer International Publishing.
  21. Ning, Z., Sun, S., Wang, X., Guo, L., Wang, G., Gao, X. and Kwok, R.Y., 2021. Intelligent resource allocation in mobile blockchain for privacy and security transactions: a deep reinforcement learning based approach. Science China Information Sciences, 64(6), p.162303.
  22. Dey, S., 2018, September. Securing majority-attack in blockchain using machine learning and algorithmic game theory: A proof of work. In 2018 10th computer science and electronic engineering (CEEC) (pp. 7-10). IEEE.
  23. Podgorelec, B., Turkanovic, M. and Karakatic, S., 2019. A machine learning-based method for automated blockchain transaction signing including personalized anomaly detection. Sensors, 20(1), p.147.
  24. Chen, T., 2022, April. Blockchain and Accounting Fraud Prevention: A Case Study on Luckin Coffee. In 2022 7th International Conference on Social Sciences and Economic Development (ICSSED 2022) (pp. 44-49). Atlantis Press.
  25. Cai, Y. and Zhu, D., 2016. Fraud detections for online businesses: a perspective from blockchain technology. Financial Innovation, 2, pp.1-10. https://doi.org/10.1186/s40854-015-0019-0
  26. Tan, B.S. and Low, K.Y., 2019. Blockchain as the database engine in the accounting system. Australian Accounting Review, 29(2), pp.312-318. https://doi.org/10.1111/auar.12278
  27. Ostapowicz, M. and Zbikowski, K., 2019. Detecting fraudulent accounts on blockchain: a supervised approach. In Web Information Systems Engineering-WISE 2019: 20th International Conference, Hong Kong, China, January 19-22, 2020, Proceedings 20 (pp. 18-31). Springer International Publishing.
  28. Huerta, E. and Jensen, S., 2017. An accounting information systems perspective on data analytics and Big Data. Journal of information systems, 31(3), pp.101-114. https://doi.org/10.2308/isys-51799
  29. Dunk, A.S., 2004. Product life cycle cost analysis: the impact of customer profiling, competitive advantage, and quality of IS information. Management accounting research, 15(4), pp.401-414. https://doi.org/10.1016/j.mar.2004.04.001
  30. Han, H., Shiwakoti, R.K., Jarvis, R., Mordi, C. and Botchie, D., 2023. Accounting and auditing with blockchain technology and artificial Intelligence: A literature review. International Journal of Accounting Information Systems, 48, p.100598.
  31. ALKAN, B.S., 2021. Real-time Blockchain accounting system as a new paradigm. Muhasebe ve Finansman Dergisi, pp.41-58.
  32. Demirkan, S., Demirkan, I. and McKee, A., 2020. Blockchain technology in the future of business cyber security and accounting. Journal of Management Analytics, 7(2), pp.189-208. https://doi.org/10.1080/23270012.2020.1731721
  33. Bonson, E. and Bednarova, M., 2019. Blockchain and its implications for accounting and auditing. Meditari Accountancy Research, 27(5), pp.725-740. https://doi.org/10.1108/MEDAR-11-2018-0406
  34. Oladejo, M.T. and Jack, L., 2020. Fraud prevention and detection in a blockchain technology environment: challenges posed to forensic accountants. International Journal of Economics and Accounting, 9(4), pp.315-335. https://doi.org/10.1504/IJEA.2020.110162
  35. Pascual Pedreno, E., Gelashvili, V. and Pascual Nebreda, L., 2021. Blockchain and its application to accounting. Intangible Capital, 17(1), pp.1-16. https://doi.org/10.3926/ic.1522
  36. Fuller, S.H. and Markelevich, A., 2020. Should accountants care about blockchain?. Journal of Corporate Accounting & Finance, 31(2), pp.34-46. https://doi.org/10.1002/jcaf.22424
  37. Abad-Segura, E., Infante-Moro, A., Gonzalez-Zamar, M.D. and Lopez-Meneses, E., 2021. Blockchain technology for secure accounting management: research trends analysis. Mathematics, 9(14), p.1631.