I build autonomous, self-correcting systems that defend against remote intrusions with minimal data or training. Since 2007, my work involved every layer of the problem, starting with hardening the system memory to give applications a solid security foundation, and designing methods for intrusion detection planning, live detection and mitigation, and adaptive system configuration. My work has grown in two further directions. The first is model-agnostic federated learning, where systems collaborate by aggregating predictions rather than training parameters. The second is the human side of security, studying cross-cultural implications of smishing attacks. Currently, I am part of a multi-university project harnessing LLMs as zero-shot classifiers to build the next generation of training-free intrusion detectors.

I am an Associate Professor and former Chair of the Department of Computer Science at Kuwait University. I earned my Ph.D. in Computer Science from Virginia Tech, where I focused on building high-assurance models for secure systems. I am a senior member of the ACM and IEEE.

I authored an open-source book on Python programming, freely available here, and have supervised several graduate theses and innovative student projects in AI, privacy, and cloud systems.

Open to research collaboration and consulting on network security and intrusion detection for web-based systems.