Triangular Pulse-Based IC Switching Current Model Using Multiple Regression Analysis for Fast Side-Channel Attack Prediction

Side-channel attacks (SCAs) pose a threat to cryptographic security by potentially recovering secret keys through the analysis of radio-frequency switching noise emitted from cryptographic integrated circuits (ICs). Predicting tolerance for SCAs enables the implementation of countermeasures in the short term. To enable fast prediction, we model the switching current transferred from the IC to the power distribution network (PDN) as a triangular pulse, subsequently applying multiple regression analysis to this pulse. As in our previous paper, we approximate the triangular pulse using register transfer level (RTL) logic simulations, which facilitate a faster prediction of the current. By applying multiple regression analysis, we can predict the SCA tolerance using a few current waveforms. To validate our model, we predicted the switching current for a field programmable gate array (FPGA) implementing the advanced encryption standard (AES) circuit, converted this into PDN noise, and then performed a primary SCA method called correlation power analysis (CPA). The results show that our method can predict PDN noise and SCA tolerance with more than a 90
$\%$
reduction in analysis time compared to the previous method.