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Myriad uses, methodologies, and channels have been explored for side-channelanalysis. However, specific implementation considerations are oftenunpublished. This paper explores select test configuration and collectionparameters, such as input voltage, shunt resistance, sample rate, andmicrocontroller clock frequency, along with their impact on side-channelanalysis performance. The analysis use case considered is instructiondisassembly and classification using the microcontroller power side-channel. AnATmega328P microcontroller and a subset of the AVR instruction set are used inthe experiments as the Device Under Test (DUT). A time-series convolutionalneural network (CNN) is used to evaluate classification performance atclock-cycle fidelity. We conclude that configuration and collection parametershave a meaningful impact on performance, especially where theinstruction-trace's signal to noise ratio (SNR) is impacted. Additionally, datacollection and analysis well above the Nyquist rate is required forside-channel disassembly. We also found that 7V input voltage with 1 kiloohmshunt and a sample rate of 250-500 MSa/s provided optimal performance in ourapplication, with diminishing returns or in some cases degradation at higherlevels.

Configuration and Collection Factors for Side-Channel Disassembly