We introduce two statistical methods for identifying recycled integrated circuits (ICs) through the use of one-class classifiers and degradation curve sensitivity analysis. Both methods rely on statistically learning the parametric behavior of known new devices and using it as a reference point to determine whether a device under authentication has previously been used. The proposed methods are evaluated using actual measurements and simulation data from digital and analog devices, with experimental results confirming their effectiveness in distinguishing between new and aged ICs and their superiority over previously proposed methods.
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Huang et al. (2015) studied this question.
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