FPIC: A Novel Semantic Dataset for Optical PCB Assurance

Abstract

Outsourced PCB fabrication necessitates increased hardware assurance capabilities. Several assurance techniques based on AOI have been proposed that leverage PCB images acquired using digital cameras. We review state-of-the-art AOI techniques and observe a strong, rapid trend toward ML solutions. These require significant amounts of labeled ground truth data, which is lacking in the publicly available PCB data space. We contribute the FPIC dataset to address this need. Additionally, we outline new hardware security methodologies enabled by our dataset.

Publication
ACM Journal on Emerging Technologies in Computing Systems
Olivia Dizon-Paradis
Olivia Dizon-Paradis
Graduate Research Assistant

My research interests include artificial intelligence, machine learning, computer vision, and reinforcement learning