Mohammed Alquraini

تخصص الأمن السيبراني · دفعة 2025

Advancing Honeypots with AI for Enhanced Cybersecurity

This project focuses on advancing the STINGAR security platform by designing and deploying new honeypot types using rapid prototyping techniques powered by large language models (LLMs). These updates will improve the detection and mitigation of cyber threats, strengthening the protection of Duke’s network and those of over 70 partner universities nationwide. Students will collaborate with Duke’s Office of Information Technology (OIT), IT Security Office (ITSO), and cybersecurity experts to research, prototype, and implement innovative honeypot designs. As a stretch goal, the team will develop mechanisms for dynamically adapting honeypots based on evolving attacker behaviors, ensuring that the system remains effective against sophisticated and emerging threats. This project provides hands-on experience with AI-driven security tools and real-world cybersecurity challenges, contributing to a cutting-edge defense network for higher education institutions.

المشرف: Hugh Thomas

اطّلع عليه في تقرير البرنامج (PDF)

تخصص الذكاء الاصطناعي · دفعة 2024

3D Printing Failure Detection and Analysis

Our deep learning model monitors 3D printing in real-time by analyzing images captured at various intervals from a camera mounted on the 3D printer. The system detects issues such as under-extrusion or spaghetti defects, allowing for early problem identification. When a defect is detected, the model sends a signal to a Raspberry Pi 4 device to halt the printing process, minimizing wasted time and materials.

اطّلع عليه في تقرير البرنامج (PDF)