The Department of Computer Science discussed the master's thesis tagged "An intelligent system for detecting fraud in distributed data on the basis of the environment using machine learning methods" for the master's student (Ashraf Tahseen Ali) Computer Science / General in the discussion room in the annex building of the Department of Computer Science. The discussion committee consisted of:

• Prof. Dr. Ahmed Tarek Sadeq, President
• Prof. Dr. Sawsan Abdel Hadi Mahmoud, Member
• Prof. Dr. Iyad Roudhan Abbas Member
• Prof. Dr. Hassanein Samir Abdullah, member and supervisor
• Dr. Mohamed Nathiq Fadel, member and supervisor

The thesis, consisting of five chapters, aims to create a multi-level system for fraud detection using machine learning and deep learning methods, based on a highly accurate decision fusion method to work within a distributed environment. The message relies on smart and flexible systems aimed at preventing the phenomenon of impersonation by relying on Identification papers (unified card) and biometric properties through the implementation of machine learning and deep learning techniques. One of the most important findings of the researcher is that despite the system's ability to detect the identity card by 100%, now the card contains some weaknesses. The (ID-CNN) build was working on all data sets in the system and gave 100% accuracy.