TREX-F: TRustability of Electronics using X-ray based Fingerprinting

The present-day electronic supply chain is infested with adversaries who threaten the integrity of electronic circuit boards and components. A major intent of such adversaries is to manufacture counterfeit printed circuit boards (PCBs). They infiltrate the supply chain with these forged PCBs, which...

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Vydané v:Digest of technical papers - IEEE/ACM International Conference on Computer-Aided Design s. 1 - 9
Hlavní autori: Sarkar, Tishya Sarma, Maitra, Shuvodip, Chakraborty, Abhishek, Bhattacharya, Sarani, Mukhopadhyay, Debdeep
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 26.10.2025
Predmet:
Authentication
Codes
Computed tomography
Data Matrix Codes
Digital Fingerprints
Feature extraction
Fingerprint recognition
Image Processing
PCB Quality Assurance
PCB Traceability
Principal component analysis
Printed Circuit Boards
Printed circuits
Protocols
Quick-Response Codes
Supply chains
X-Ray Computed Tomography
X-ray imaging
ISSN:1558-2434
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Shrnutí:The present-day electronic supply chain is infested with adversaries who threaten the integrity of electronic circuit boards and components. A major intent of such adversaries is to manufacture counterfeit printed circuit boards (PCBs). They infiltrate the supply chain with these forged PCBs, which closely mimic the original designs, albeit jeopardizing the business cycle of electronic design. In this work, we aim to restrict the circulation of tampered and counterfeit boards in the supply chain by leveraging the inherent physical deformities of authentic PCBs, which are difficult to replicate. Such anomalies include solder defects, material deposition, and microscopic irregularities unique to each PCB. These anomalies, though imperceivable to the human eye, can be captured at a specific angle under an X-ray microscope when imaged at appropriate orientations. Our proposed framework, TREX-F, comprises an image-based authentication protocol that defines unique fingerprints of each PCB by extracting such anomalies and converting them into quick-response and data-matrix codes. We construct device-specific templates from the X-ray computed tomography slices of the PCB samples by utilizing a combination of computer vision techniques, including Canny edge detection, contour detection, principal component analysis, and scale-invariant feature transform. As a case study, we validate our framework on Arduino UNO, Raspberry Pi 4 model B, and STM32F407G boards. TREX-F enables a sustainable electronics supply chain ecosystem, wherein end users can directly verify the authenticity of the procured PCBs with an average accuracy of ≥95% across all boards, and an average false acceptance rate (FAR) of 0. 1
ISSN:1558-2434
DOI:10.1109/ICCAD66269.2025.11240899