Integrated Circuit (IC) manufacturing leverages a global supply chain to maintain economic competitiveness. Modularization of the manufacturing workflow leaves it vulnerable to malicious attacks. For instance, untrusted foundries may deliberately install backdoors, i.e. hardware Trojans, into cyber systems for an adversary to exploit at will, or the circuit design–the IP of the designer–maybe stolen and duplicated. Reverse Engineering (RE) is the only approach for security experts to verify IC design, detect stolen IP, and, potentially, guarantee trust in the device. However, the existing RE process is ad-hoc, unscalable, error-prone, and requires manual intervention by subject matter experts, thereby limiting its potential as the go-to tool for hardware assurance. 

This thrust currently focuses on resolving these limitations by developing critical algorithmic infrastructure to advance automation in the IC RE process. This project uses concepts from image processing, computer vision, ML, and AI to acquire, process, and gain insights from electron microscopy images of the IC and further develop AI-driven security policy for generating RE-compliant IC design for seamless cost/time-efficient design verification. The knowledge gained through this project will also be disseminating through educational programs and collaborations with the semiconductor industry.