Researcher “Al Sharif Hassan” Abu Rbian, a student in the master’s program in Cyber Security has defended his thesis titled: “Securing Financial Transactions via the Internet Using Multi-Factor Authentication and Machine Learning.”
The research deals the problem of the security of online financial transactions as a serious concern in an era in which digital financial services are being increasingly used. The increasing use of digital platforms for banking, payments and investment has created a new opportunities for hackers. In order to address this problem, the current study presents a unique system that integrates machine learning (ML) with multi-factor authentication (MFA). The first layer uses two-factor authentication, and the second is an embedded layer that requires facial recognition by the user to successfully continue the purchase process if the machine learning model determines that the current transaction is suspected to be fraudulent.
A comprehensive analysis of the research papers conducted on this topic and different approaches to securing online transactions reveals that the integration of multi-factor authentication and the use of machine learning have great potential to provide the highest level of security.
The thesis was supervised by Prof. Dr. Manuel Fernández-Veiga. The committee of examiners included: Dr. Majdi Owda and Prof. Dr. Ana Fernández Vilas.
