About Us
The Computer Security Research Lab (CSRL) conducts research on the security of computer systems, with a scope that includes personal computers, computer networks, smartphones, wearable devices, and Internet of Things (IoT) devices. Our research improves protections against cyberthreats that target computer systems and their users. Our research group is led by Prof. Furkan Alaca and we are located at 624 Goodwin Hall at the Queen's University School of Computing.
News
Congratulations to Jacqueline Chan for successfully defending her MSc thesis! Jacqueline's thesis, titled "Threshold-Based Password Management with Trusted Execution Environments", uses Trusted Execution Environements (TEEs) and threshold cryptography to protect passwords against compromised personal devices and enable secure sharing of secrets with other users.
Congratulations to Siam Antar for successfully defending his MSc thesis! Siam's thesis, titled "Pioneering Autonomous Penetration Testing With Large Language Models Through Prompt Engineering and Agentic System Design", introduces a phase-driven prompting methodology to guide LLMs through the Cyber Kill Chain. His research demonstrates the viability of LLM-assisted autonomous penetration testing and continuous cybersecurity posture monitoring.
Congratulations to Aadarsh Sreekumar for the successful completion of his MSc project! Aadarsh's project, titled "A Verifiable Delivery Framework for Web Applications That Use Trusted Execution Environments", leverages Meta's Code Verify browser extension to implement trustworthy delivery and client-side verifiability for web applications that rely on server-side Trusted Execution Environments (TEEs) to provide security guarantees.
Congratulations to Nafiz Sadman for successfully defending his MSc thesis! Nafiz's thesis, titled "DepthPulse: A Passive Liveness Detection Framework for Face Presentation Attacks", contributes to strengthening face-recognition based user authentication systems against presentation attacks (also known as spoofing attacks).
Congratulations to Christopher Molloy for successfully defending his PhD thesis! Chris' thesis, titled "Adversarial Learning for Cyber Threat Intelligence: An Attention on Malware", proposes novel deep-learning based techniques to defend computer systems against malware.