Master’s Degree Awarded to Mr. Abdulrahman Hussein Hashem Al-Hames in Computer Science

Mr. Abdulrahman Hussein Hashem Al-Hames was awarded a Master’s Degree in Computer Science for his thesis titled: A Hybrid Deep Learning Approach for Secure Biometric Authentication Using Fingerprint Data, which was submitted to the Department of Computer Science, Faculty of Computer and Information Technology – Sana’a University. The MA defense was held on Monday, Sha’ban 28, 1447 Hijri, corresponding to February 16, 2026‎.

The MA Viva-voce Committee, which was formed based on a resolution issued by the Graduate Studies and Scientific Research Council, consisted of the following:
# Committee Members Designation Position
1 Prof. Mansour Othman Marhoob ‎ Internal Examiner Chair
2 Prof. Fouad Morshed ‎ ‎ Main Supervisor Member
3 Associate Prof. Adel Abdulsalam Al-Shamiri ‎ External Examiner Member

The thesis aimed to develop a hybrid model based on deep learning techniques to enhance security in biometric authentication systems using fingerprint data, by integrating multiple deep learning networks to improve verification accuracy, reduce error rates, and increase system reliability in sensitive security environments.
The study yielded several key findings summarized as follows:
 The study achieved a high verification accuracy rate using the proposed model.‎
 There was a reduction in False Acceptance Rate (FAR) and False Rejection Rate ‎‎(FRR) compared to traditional models.‎
 It improved system efficiency in processing fingerprint data and reduced response ‎time.‎
 The study demonstrated effectiveness of integrating deep learning techniques in ‎enhancing biometric security levels.‎
In light of these findings, the researcher recommended the following:
 Expanding the use of hybrid models in other biometric authentication systems.‎
 Studying the application of the model on larger and more diverse databases.‎
 Developing additional protection mechanisms to enhance fingerprint data storage ‎security.‎
 Employing explainable AI techniques to increase the reliability of security systems.‎
The defense session was attended by a number of academics, researchers, students, colleagues, and the researcher’s family.