RHU proudly celebrates a remarkable academic and research achievement as a senior graduation project developed by students from the Computer and Communications Engineering program has been officially published and indexed in the prestigious IEEE Xplore Digital Library after its successful presentation at the IEEE-IMCET 2026 conference.
The research paper, titled “An Efficient AI-Driven Intrusion Detection System for Resource-Constrained IoT Environments,” was authored by RHU CCE alumni Asmaa Hindawi and Fouad Naffah, along with students Omar Al Halabi and Souad Al Sabouh, under the supervision of RHU lecturer Ms. Amal El Arid.
As smart cities, connected systems, and intelligent homes continue to expand worldwide, securing low-power IoT devices has become one of the most pressing cybersecurity challenges. To address this critical issue, the RHU research team developed an innovative AI-powered intrusion detection framework for resource-constrained environments, delivering exceptional security performance without compromising device efficiency.
By leveraging optimized XGBoost and Extra Trees machine learning algorithms, the system achieved an impressive detection accuracy of 99.25%. The framework was engineered to run efficiently on low-power IoT infrastructure, ensuring robust protection with minimal hardware strain. Through seamless integration with Suricata and Telegram APIs, the system also delivers real-time alerts with end-to-end latency of only 1.2 seconds.
This accomplishment reflects RHU’s ongoing commitment to academic excellence, innovation, and applied research addressing real-world challenges. By transforming a senior graduation project into a globally recognized IEEE publication, RHU students continue to demonstrate their ability to contribute meaningfully to the future of cybersecurity, artificial intelligence, and smart technologies.
Access the full publication on IEEE Xplore: IEEE Xplore Publication