A Novel Framework for Identifying Counterfeit ICs via Pinhole Evaluation
Counterfeit ICs jeopardize safety in high-reliability sectors. We propose a non-destructive pinhole inspection framework to detect counterfeit coatings such as blacktop fills, splatter marks, and coating droop enabling automated, scalable solutions with deep learning. This approach advances industry-wide counterfeit mitigation and preserves system performance.
Authors
- Chih‐Hao Pai (ORCID: https://orcid.org/0000-0002-1223-4053)
- Shajib Ghosh (ORCID: https://orcid.org/0000-0003-3523-8177)
- Chi‐Hsiang Huang (ORCID: https://orcid.org/0000-0001-5357-0451)
- Navid Asadizanjani (ORCID: https://orcid.org/0000-0002-7097-4463)
- Patrick J Craig
- Md Shah Imran Shovon
Institutions
- Odessa College (US)
- University of Florida (US)
Publication Details
- Published
- 2025-08-13
- DOI
- https://doi.org/10.1109/rapid64712.2025.11151374
- Primary Topic
- Physical Unclonable Functions (PUFs) and Hardware Security
- Type
- article
- Field-Weighted Citation Impact
- 0.00