THz testing has been recently proposed to identify altered or damaged ICs. This method is based on the fact that a modern field-effect transistor (FET) with a sufficiently short channel can serve as a terahertz detector. The response can be recorded while changing the THz radiation parameters and location and compared to a trusted one for classification. We measured the THz response of original and damaged ICs for classification using different Transfer Learning models as a method of deep learning. We have achieved the highest classification accuracy of 98%.
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