Reverse Engineering of Printed Electronics Circuits: From Imaging to Netlist Extraction

Printed electronics (PE) circuits have several advantages over silicon counterparts for the applications where mechanical flexibility, extremely low-cost, large area, and custom fabrication are required. The custom (personalized) fabrication is a key feature of this technology, enabling customizatio...

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Bibliographic Details
Published in:IEEE transactions on information forensics and security 2020, Vol.15, p.475-486
Main Authors: Erozan, Ahmet Turan, Hefenbrock, Michael, Beigl, Michael, Aghassi-Hagmann, Jasmin, Tahoori, Mehdi B.
Format: Article
Language:English
Subjects:
Circuit design
Computer engineering
Design standards
Electronics
Fabrication
Image acquisition
Integrated circuits
Layout
Low cost
Machine learning
personal fabrication
Printed electronics
Printing
Reverse engineering
Silicon
supervised learning
Transistors
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Summary:Printed electronics (PE) circuits have several advantages over silicon counterparts for the applications where mechanical flexibility, extremely low-cost, large area, and custom fabrication are required. The custom (personalized) fabrication is a key feature of this technology, enabling customization per application, even in small quantities due to low-cost printing compared with lithography. However, the personalized and on-demand fabrication, the non-standard circuit design, and the limited number of printing layers with larger geometries compared with traditional silicon chip manufacturing open doors for new and unique reverse engineering (RE) schemes for this technology. In this paper, we present a robust RE methodology based on supervised machine learning, starting from image acquisition all the way to netlist extraction. The results show that the proposed RE methodology can reverse engineer the PE circuits with very limited manual effort and is robust against non-standard circuit design, customized layouts, and high variations resulting from the inherent properties of PE manufacturing processes.
ISSN:1556-6013
1556-6021
DOI:10.1109/TIFS.2019.2922237