As part of the graduation project defenses for the Cybersecurity program (2025-2026), and in the presence of IUTT President Prof. Dr. Wael Al-Aghbari, Vice President Prof. Dr. Sadiq Manna, and Secretary-General Dr. Abdullah Jahaaf, the Faculty of Computer Science showcased a distinguished project titled: Real-Time Network Intrusion Prevention System Based on Machine Learning.
The project introduces a comprehensive engineering solution to network security challenges, implementing a real-time intrusion prevention system based on a hybrid machine learning methodology. The system utilizes a dual-level classification architecture (Decision Tree and Random Forest), achieving a processing speed of up to 1.2 million packets per second with a detection accuracy exceeding 97%.
Developed using Python, Node.js, and Vue.js, with real-time updates via WebSocket, the project reflects an advanced integration of AI and modern security systems.
Project Team: (Aidrous Shaafan, Ali Al-Sayyad, Salahuddin Al-Ansi, Yousef Shehdi, Mohammad Al-Athouri, Hashem Al-Kuhlani) supervised by Dr. Hesham Aqlan.
Defense Committee: (Dr. Hamzah Jamel, Dr. Jameel Hamzah, Dr. Amin Shayae, Dr. Abduljabbar Al-Sharif).
