Machine Learning Assisted Counterfeit IC Detection through Non-destructive Infrared (IR) Spectroscopy Material Characterization
Author:
Affiliation:
1. University of Florida,Florida Institute of Cyber Security,Gainesville,FL-32608
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9816066/9816372/09816472.pdf?arnumber=9816472
Reference21 articles.
1. Survey of high-temperature polymeric encapsulants for power electronics packaging;yao;IEEE Trans Components Packag Manuf Technol,2015
2. Characterization of plastic encapsulant materials as a baseline for quality assessment and reliability testing
3. FTIR Method to Distinguish Mold Compound Types and Identify the Presence of Post-Mold-Cure (PMC) Treatment on Electronic Packaging
4. Effects of Storage Aging on the Properties of Epoxy Prepregs
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1. AutoDetect: Novel Autoencoding Architecture for Counterfeit IC Detection;Journal of Hardware and Systems Security;2024-05-23
2. Enhancing counterfeit detection of integrated circuits through machine learning-assisted THz-TDS analysis;Terahertz, RF, Millimeter, and Submillimeter-Wave Technology and Applications XVII;2024-03-11
3. THz-TDS for IC packaging material changes detection under real-world conditions;Terahertz, RF, Millimeter, and Submillimeter-Wave Technology and Applications XVII;2024-03-11
4. Automated Transfer Learning Model for Counterfeit IC Detection;2022 IEEE Physical Assurance and Inspection of Electronics (PAINE);2022-10-25
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