Better Side-Channel Attacks Through Measurements

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In recent years, there has been a growing focus on improving the efficiency of the power side-channel analysis (SCA) attack by using machine learning or artificial intelligence methods, however, they can only be as good as the data they are trained on. Previous work has not given much attention to improving the accuracy of measurements by optimizing the measurement setup and the parameters, and most new researchers rely on heuristics to make measurements. This paper proposes an effective methodology to launch power SCA and increase the efficiency of the attack by improving the measurements. We examine the heuristics related to measurement parameters, investigate ways to optimize the parameters, determine their effects empirically, and provide a theoretical analysis to support the findings. To demonstrate the shortcomings of commercial measurement devices, we present a low-cost measurement board design and its hardware realization. In doing so, we are able to improve the power measurements, by optimizing the measurement setup, which in turn improves the efficiency of the attack.