Preprint Review Version 1 This version is not peer-reviewed

Using Machine Learning and Deep Learning to Strengthen Bangladesh’s Financial Infrastructure for Banking Cybersecurity

Version 1 : Received: 5 September 2024 / Approved: 9 September 2024 / Online: 9 September 2024 (11:24:39 CEST)

How to cite: Biplob, M. B.; Bhuiyan, T.; Farabi, A. M. Using Machine Learning and Deep Learning to Strengthen Bangladesh’s Financial Infrastructure for Banking Cybersecurity. Preprints 2024, 2024090645. https://doi.org/10.20944/preprints202409.0645.v1 Biplob, M. B.; Bhuiyan, T.; Farabi, A. M. Using Machine Learning and Deep Learning to Strengthen Bangladesh’s Financial Infrastructure for Banking Cybersecurity. Preprints 2024, 2024090645. https://doi.org/10.20944/preprints202409.0645.v1

Abstract

Currently, the Bangladeshi financial sector is undergoing significant transformations. With the expansion of the infrastructure and the increasing prevalence of digital banking services, it is essential to take measures to prevent cyberattacks. These threats can be effectively mitigated through the utilization of deep learning and machine learning techniques. Through the analysis of massive amounts of banking data in real-time, these methods make it possible to detect and prevent malicious software, fraud, and security breaches that are proactive. Because the government is actively pushing for financial inclusion and digitalization, strong cybersecurity measures are more important than they have ever been. It is the purpose of this study to investigate the application of deep learning and machine learning to improve the cybersecurity environment of Bangladesh’s banking sector in light of the country’s rapidly expanding digital economy.

Keywords

financial-sector; breaches; bangladesh; cyberattacks; deep-learning; machine-learning; fraud; cybersecurity; digital-banking; malware; banking-data; Realtime-analysis; financial-inclusion; digitalization

Subject

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

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