Outsourced printed circuit board (PCB) fabrication necessitates increased hardware assurance capabilities. Several assurance techniques based on automated optical inspection (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 machine learning (ML) solutions. These require significant amounts of labeled ground truth data, which is lacking in the publicly available PCB data space. We contribute the FICS PCB Image Collection (FPIC) dataset to address this need. Additionally, we outline new hardware security methodologies enabled by our data set.
@article{arxiv.2202.08414,
title = {FPIC: A Novel Semantic Dataset for Optical PCB Assurance},
author = {Nathan Jessurun and Olivia P. Dizon-Paradis and Jacob Harrison and Shajib Ghosh and Mark M. Tehranipoor and Damon L. Woodard and Navid Asadizanjani},
journal= {arXiv preprint arXiv:2202.08414},
year = {2023}
}
Comments
Dataset is available at https://www.trust-hub.org/#/data/pcb-images ; Submitted to ACM JETC in Feb 2022; Accepted February 2023