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The edge devices in an emerging Internet-of-Things (IoT) environment require comprehensive security measures that are within the power budget for ubiquitous computing. In this paper, a transmitter identification scheme consisting of a lightweight Bayesian neural network (BNN)based classifier using raw time-domain data is presented. Evaluation is performed with data obtained in schematic-level simulation of high-efficiency CMOS power amplifier designs using a 65 nm process design kit (PDK). Thedoi:10.1109/ojcas.2021.3089499 fatcat:plswd32bezc3znc5dl22pxhmdi