Techniques for foundry identification

Foundry identification is essential for many tasks including intellectual property protection, trust, and preventing counterfeiting. In this paper, we introduce statistical techniques for foundry detection, specifically for identifying from which foundry a particular chip originates from. The key idea is to consider the distributions of channel lengths and threshold voltages after employing a variant of SAT that extracts these two metrics. We apply Kolmogorov-Smirnov and other statistical tests for comparing the two empirical distributions. Finally, we study the effects of sample size and measurement error on the correct identification rate and establish an interval of confidence using resubstitution techniques.