The student Jamal Helal Asi received his PhD degree from Computer Sciences department / University of Technology for his thesis titled (Intrusion Detection Analysis using Machine Learning and Improved Artificial Immune System). In this thesis, the Dataset was reduced from 41 to 10 important properties, the accuracy was high (84.1509%) and the time was (6.11 seconds) with the classification algorithm (J48). The second proposal is the AIRS algorithm, , The proposed system is the VNS classification. The principle of this algorithm is the successive detection of the neighbors to find the best solutions and produce a set of real vectors ready for classification. The results are based on NSL-KDD dataset and showed an increase in performance accuracy compared to the original algorithm (AIRS). The result was (88.136% 9872.15 seconds). In the third proposal, AIRS is an advanced algorithm developed by AIRS. It was suggested to improve the performance of the AIRS input and copy cells, which would give the best cells that can be compared to patterns in the data set.

This was on Sunday, September 30, 2018, and on the discussion room in the annex building of the department. The discussion committee was composed of: Dr. Soukaina Hassan Hashim, Dr. Alaa Kazem Farhan, (From the University of Technology / Computer Science Department and Prof. Dr. Mahmoud Khalil Ibrahim) from the University of Nahrain / Information Engineering and (Dr. Nada Abdel-Zahra Abdullah) from the University of Baghdad / Faculty of Science / Department of Computer Science In the presence of the student supervisor (Prof. Ahmed Tariq Sadiq).

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