College of Computer Science and Mathematics

Discussion of the master’s thesis in the College of Computer Science and Mathematics – Department of Software Department entitled: Design and Implementation  of a tool for Android malware applications analysis

Master’s thesis by Omar Emad Saied

Supervised by Assist Prof. Dr. Karam Hatem Thanoon

The Master’s thesis addressed the development of an intelligent tool for analyzing and detecting malicious applications in the Android operating system by integrating static analysis and dynamic analysis within a unified framework. The tool aims to enhance cybersecurity by improving the accuracy of malware detection and supporting users and researchers with real-time prediction of new applications.

The study relied on designing and constructing two customized datasets consisting of benign and malicious applications. For building the classification model, the proposed tool combined machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM), and Decision Tree (DT).

The results demonstrated a high accuracy exceeding 95%, confirming the effectiveness of the tool in reducing errors and improving the reliability of malware detection. The thesis concluded that integrating static and dynamic analysis with artificial intelligence represents an important step toward building flexible and scalable detection systems to address the growing threats in the Android environment.

The discussion committee consists of

Assistant Prof. Dr. Qutaiba Abdullah Hassan (Chair)
Assistant Prof. Dr. Saadoun Hussein Abdullah (Member)
Assistant Prof. Dr. Muna Mohammed Taher (Member)
Assistant Prof. Dr. Karam Hatem Thanoon (Member and Supervisor)