Blockchain-Enabled Cybersecurity In Banking Systems: A Survey Of Current Practices
Main Article Content
Abstract
The fast digitalization of bank services has exposed financial institutions in the global market to such cyber threats and thus, cybersecurity has become a burning issue in the financial sector. Conventional centralized security systems can hardly handle such issues as data corruption, fraud, identity theft, and system failure in response to more advanced cyberattacks. Here, blockchain technology has risen as a viable option to improve cybersecurity of banking systems because it has a decentralized, immutable, and cryptographically secured structure. The paper is a critical analysis of blockchain-based cybersecurity in the banking industry that analyzes the basic principles of blockchain technology, cybersecurity needs in banking system, and application of blockchain in security. The paper explains the possibility of providing confidentiality and integrity of data in addition to minimizing single point of failure through the use of distributed ledger technology and cryptographic methods. It also examines the use of blockchain in securing financial transactions, enhancing fraud detection and prevention, and providing the opportunity to manage the identity with the help of Know Your Customer (KYC) and Anti-Money Laundering (AML) compliance. The literature review outlines an in-depth research of blockchain-based security solutions, AI-based threat detection and classification of cyber threats in the banking setting. The results show that blockchain has the potential to substantially increase the levels of trust, transparency, and resilience in digital banking systems, but such issues as scalability, regulatory adherence, and large-scale usability still exist. The paper has ended by highlighting the possibilities of blockchain as a supplementary cybersecurity framework in current banking ecosystems
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Download CopyrightReferences
[1] F. Jimmy, “Cybersecurity Threats and Vulnerabilities in Online Banking Systems,” Int. J. Sci. Res. Manag., vol. 12, no. 10, pp. 1631–1646, Oct. 2024, doi: 10.18535/ijsrm/v12i10.ec10.
[2] G. Sarraf and V. Pal, “Autonomous Threat Detection and Response in Cloud Security: A Comprehensive Survey of AI-Driven Strategies,” Int. J. Emerg. Res. Eng. Technol., vol. 6, no. 4, 2025, doi: 10.63282/3050-922X.IJERET-V6I4P114.
[3] T. Shah, “Leadership in digital transformation: Enhancing customer value through AI-driven innovation in financial services marketing,” Int. J. Sci. Res. Arch., vol. 15, no. 3, pp. 618–627, Jun. 2025, doi: 10.30574/ijsra.2025.15.3.1767.
[4] I. P. Mandliya, “A Study On Cyber Security Affecting Online Banking And Online Transaction,” 2023.
[5] S. Thangavel, S. Srinivasan, S. B. V. Naga, and K. Narukulla, “Distributed Machine Learning for Big Data Analytics: Challenges, Architectures, and Optimizations,” Int. J. Artif. Intell. Data Sci. Mach. Learn., vol. 4, no. 3, pp. 18–30, Oct. 2023, doi: 10.63282/3050-9262.IJAIDSML-V4I3P103.
[6] S. Narang and A. Gogineni, “Zero-Trust Security in Intrusion Detection Networks: An AI-Powered Threat Detection in Cloud Environment,” Int. J. Sci. Res. Mod. Technol., vol. 4, no. 5, pp. 60–70, Jun. 2025, doi: 10.38124/ijsrmt.v4i5.542.
[7] K. S. Hebbar, “Optimizing Distributed Transactions in Banking APIs: Saga Pattern vs. Two-Phase Commit (2PC),” Am. J. Eng. Technol., vol. 7, no. 06, pp. 157–169, 2025, doi: 10.37547/tajet/Volume07Issue06-18.
[8] V. Verma, “Deep Learning-Based Fraud Detection in Financial Transactions : A Case Study Using Real-Time Data Streams,” vol. 3, no. 4, pp. 149–157, 2023, doi: 10.56472/25832646/JETA-V3I8P117.
[9] P. Ogeti, N. S. Fadnavis, G. B. Patil, U. K. Padyana, and H. P. Rai, “Blockchain Technology for Secure and Transparent Financial Transactions,” Eur. Econ. Lett., vol. 12, no. 2, p. 9, 2022.
[10] P. Gupta, S. Kashiramka, and S. Barman, “A Practical Guide for Ethical AI Product Development,” in 2024 IEEE 11th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), IEEE, Nov. 2024, pp. 1–6. doi: 10.1109/UPCON62832.2024.10983504.
[11] R. Dattangire, R. Vaidya, D. Biradar, and A. Joon, “Exploring the Tangible Impact of Artificial Intelligence and Machine Learning: Bridging the Gap between Hype and Reality,” in 2024 1st International Conference on Advanced Computing and Emerging Technologies (ACET), IEEE, 2024, pp. 1–6. doi: 10.1109/ACET61898.2024.10730334.
[12] S. Yadav, “Role of Blockchain Technology in Enhancing Cybersecurity,” Int. J. LAW Manag. Humanit., vol. 8, no. 3, p. 10, 2025.
[13] M. Birje, R. H. Goudar, R. C. M, and M. T. Tapale, “Blockchain Technology Review: Consensus Mechanisms and Applications,” Int. J. Eng. Trends Technol., vol. 71, no. 5, pp. 27–39, May 2023, doi: 10.14445/22315381/IJETT-V71I5P204.
[14] R. Soltani, M. Zaman, R. Joshi, and S. Sampalli, “Distributed Ledger Technologies and Their Applications: A Review,” Appl. Sci., vol. 12, no. 15, p. 7898, Aug. 2022, doi: 10.3390/app12157898.
[15] S. Ahmad, S. K. Arya, S. Gupta, P. Singh, and S. K. Dwivedi, “Study of Cryptographic Techniques Adopted in Blockchain,” in 2023 4th International Conference on Intelligent Engineering and Management (ICIEM), IEEE, May 2023, pp. 1–6. doi: 10.1109/ICIEM59379.2023.10166591.
[16] B. Kieu-Do-Nguyen, C. Pham-Quoc, N.-T. Tran, C.-K. Pham, and T.-T. Hoang, “Low-Cost Area-Efficient FPGA-Based Multi-Functional ECDSA/EdDSA,” Cryptography, vol. 6, no. 2, p. 25, May 2022, doi: 10.3390/cryptography6020025.
[17] N. M. Nasir, S. Hassan, and K. Mohd Zaini, “Securing Permissioned Blockchain-Based Systems: An Analysis on the Significance of Consensus Mechanisms,” IEEE Access, vol. 12, pp. 138211–138238, 2024, doi: 10.1109/ACCESS.2024.3465869.
[18] A. R. Bilipelli, “Forecasting the Evolution of Cyber Attacks in FinTech Using Transformer-Based Time Series Models,” Int. J. Res. Anal. Rev., vol. 10, no. 3, pp. 383–389, 2023.
[19] A. Anyanwu, T. Olorunsogo, T. O. Abrahams, and O. J. Akindote, “ata Confidentiality And Integrity: A Review Of Accounting And Cybersecurity Controls In Superannuation Organizations,” Comput. Sci. IT Res. J., vol. 5, no. 1, pp. 237–253, Jan. 2024, doi: 10.51594/csitrj.v5i1.735.
[20] S. K. Chintagunta and S. Amrale, “Enhancing Cloud Database Security Through Intelligent Threat Detection and Risk Mitigation,” Tech. Int. J. Eng. Res., vol. 9, no. 10, pp. 49–55, 2022, doi: 10.56975/tijer.v9i10.159996.
[21] N. Prajapati, “Federated Learning for Privacy-Preserving Cybersecurity : A Review on Secure Threat Detection,” Int. J. Adv. Res. Sci. Commun. Technol., vol. 5, pp. 520–528, 2025, doi: 10.48175/IJARSCT-25168.
[22] E. McCoy, “Cybersecurity Regulations and Risk Management in the Financial Sector: A Comparative Analysis,” Law, Econ. Soc., vol. 1, no. 1, p. p115, 2025, doi: 10.30560/les.v1n1p115.
[23] A. Parupalli, “Business Intelligence in ERP ML-Based Comparative Study for Financial Forecasting,” ESP Int. J. Commun. Eng. Electron. Technol., vol. 2, no. 4, pp. 17–26, 2024, doi: 10.56472/25839217/IJCEET-V2I4P103.
[24] V. Prajapati, “Enhancing Threat Intelligence and Cyber Defense through Big Data Analytics: A Review Study,” J. Glob. Res. Math. Arch., vol. 12, no. 4, 2025.
[25] D. Patel, “Enhancing Banking Security: A Blockchain and Machine Learning- Based Fraud Prevention Model,” Int. J. Curr. Eng. Technol., vol. 13, no. 06, pp. 576–583, 2023, doi: 10.14741/ijcet/v.13.6.10.
[26] S. B. Karri, S. Gawali, S. Rayankula, and P. Vankadara, “AI Chatbots in Banking: Transforming Customer Service and Operational Efficiency,” in Advancements in Smart Innovations, Intelligent Systems, and Technologies, 2025, pp. 61–81. doi: 10.3233/FAIA251498.
[27] A. Roy and S. S. Tinny, “Cybersecurity and Blockchain for Secure Financial Transactions: Evaluating, Implementing, and Mitigating Risks of Digital Payments,” Int. J. Appl. Nat. Sci., vol. 1, no. 2, pp. 38–48, Aug. 2024, doi: 10.61424/ijans.v1i2.95.
[28] H. Patel, O. Patil, M. Makandar, and R. Patel, “Enhancing Money Transaction Security Through Blockchain Technology : A Comprehensive review and Analysis,” 2024. doi: 10.2139/ssrn.4963437.
[29] S. R. Kurakula, “Designing Enterprise Systems for the Future of Financial Services: The Intersection of AI, Cloud-Native Microservices, and Intelligent Data Processing,” Eur. J. Comput. Sci. Inf. Technol., vol. 13, no. 20, pp. 91–103, 2025.
[30] M. S. Parvez and M. R. Khan, “The Role of Blockchain in Banking Fraud Detection: Enhancing Security and Transparency,” J. Comput. Sci. Technol. Stud., vol. 7, no. 2, pp. 386–394, Apr. 2025, doi: 10.32996/jcsts.2025.7.2.40.
[31] H. P. Kapadia, “CDN Strategies for Secure and Fast Banking Services,” Int. J. Curr. Sci., vol. 12, no. 4, pp. 863–869, 2022.
[32] S. J. Wawge, “A Survey on the Identification of Credit Card Fraud Using Machine Learning with Precision, Performance, and Challenges,” Int. J. Innov. Sci. Res. Technol., vol. 10, no. 4, pp. 3345–3352, May 2025, doi: 10.38124/ijisrt/25apr1813.
[33] R. Palwe, “Adaptive human: AI decision support for high-stakes financial advice,” Int. J. Comput. Artif. Intell., vol. 6, no. 2, pp. 385–392, Jul. 2025, doi: 10.33545/27076571.2025.v6.i2e.226.
[34] O. M. Eseoghnene, “Applying Blockchain-Based Fraud Prevention Mechanisms for Securing Digital Banking Transactions and Strengthening Customer Trust in Financial Institutions Worldwide,” Int. J. Res. Publ. Rev., vol. 6, no. 9, pp. 351–367, Sep. 2025, doi: 10.55248/gengpi.6.0925.3334.
[35] D. Tonnonlah, S. F. Juma, S. Yandokoye, and A. Pandey, “Cybersecurity Threats in IoT-Enabled Banking: Survey & Solutions,” in 2025 International Conference on Intelligent and Secure Engineering Solutions (CISES), IEEE, Aug. 2025, pp. 610–619. doi: 10.1109/CISES66934.2025.11265429.
[36] T. Roy, M. I. Alam, A. Turag, S. R. Chowdhury, and A. Kafi, “Securing Blockchain in Banking: Cyber Threat Mitigation,” in 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE), IEEE, Feb. 2025, pp. 1–4. doi: 10.1109/ECCE64574.2025.11013217.
[37] V. Paul and P. Kulkarni, “Integration of Blockchain Technology and Machine Learning in Online Secure Banking System,” in 2024 8th International Conference on Computational System and Information Technology for Sustainable Solutions (CSITSS), IEEE, Nov. 2024, pp. 1–4. doi: 10.1109/CSITSS64042.2024.10816977.
[38] V. Nakonechnyi, S. Toliupa, V. Saiko, V. Lutsenko, G. S. N. Ghno, and A. K. Hussain, “Blockchain Implementation in the Protection System of Banking System During Online Banking Operations,” in 2024 35th Conference of Open Innovations Association (FRUCT), IEEE, Apr. 2024, pp. 492–500. doi: 10.23919/FRUCT61870.2024.10516404.
[39] A. A. Darem, A. A. Alhashmi, T. M. Alkhaldi, A. M. Alashjaee, S. M. Alanazi, and S. A. Ebad, “Cyber Threats Classifications and Countermeasures in Banking and Financial Sector,” IEEE Access, vol. 11, pp. 125138–125158, 2023, doi: 10.1109/ACCESS.2023.3327016.
[40] S. Dasgupta, B. V. Yelikar, Ramnarayan, S. Naredla, R. K. Ibrahim, and M. B. Alazzam, “AI-Powered Cybersecurity: Identifying Threats in Digital Banking,” in 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), IEEE, May 2023, pp. 2614–2619. doi: 10.1109/ICACITE57410.2023.10182479.