The RoboInsight (formerly AutoInsight) project utilizes advanced techniques in software security, control system modeling, and system replay to develop a new security analysis platform for modern robotic and autonomous systems, including robotic arms, mobile robots, and autonomous vehicles.

The AI Vault project designs and develops new trusted execution environments tailored to run artificial intelligence and machine learning programs on modern AI platforms, including cloud platforms and embedded devices, while providing strong data confidentiality and high efficiency.

Robotic vehicles (also known as drones) are facing various threats of cyber-physical attacks that exploit their security vulnerabilities. RetroV develops automated analysis tools to find such vulnerabilities in existing robotic vehicle systems and retrofit their design against advanced cyber-physical attacks.

The CLUE project develops an infrastructure to detect and diagnose system anomalies in enterprise and cloud systems. These anomalies include stealthy malware and other types of hidden system anomalies. CLUE provides a diverse set of tools to find and understand such anomalies with minimal disruption to the target system.

The RetroFirm project aims to enhance the security of existing embedded devices by creating retrospective methods for firmware analysis and vulnerability detection.