A Comprehensive Taxonomy of Visual Printed Circuit Board Defects

Abstract

The globalization of printed circuit board (PCB) production has expanded the avenues to introduce vulnerabilities into the electronics supply chain. Malicious parties may modify or alter PCBs to purposely compromise the integrity of a design. In contrast, non-malicious incidents may also change an ideal design; they unintentionally lead to defects. For the reverse engineering process, which requires precise information to replicate a design, these deviations from the intended design present an overwhelming challenge. Although they are primarily unintentional, defects may cause a device to stray from its intended functionality, and present danger to both manufacturers and consumers. Therefore, irrespective of their cause and effect, the PCB inspection industry requires intricate knowledge of their occurrences; defects must be correctly enumerated before satisfactory solutions can be proposed. This article presents an extensive taxonomy of physical defects in PCBs that can be primarily identified using automated optical inspection (AOI), or traditional visual inspection methods where applicable. Our goal is to ultimately improve the state of hardware security by providing a guide to physical defects. To the best of our knowledge, this is the first comprehensive taxonomy of visual PCB defects.

Publication
Springer Journal of Hardware and Systems Security
Olivia Dizon-Paradis
Olivia Dizon-Paradis
Graduate Research Assistant

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