Channel Equalization for Side Channel Attacks

This paper introduces the use of channel equalization as a method of reducing the computational complexity of side channel analysis (SCA), by effectively collapsing all points in a power measurement trace into a single random variable. This uses a simple Finite Impulse Response (FIR) linear equalizer, which has been studied extensively in communications systems. In addition the estimation of a channel model is used in developing the Channel Estimation Analysis (CEA), which is a generic attack requiring similar assumptions to the Correlation Power Analysis (CPA) attack. Both channel equalization and the CEA attack are straight-forward to apply to real systems, and Python examples are provided. Results of attacking unprotected AES-128 and protected AES256RSM on a microcontroller are provided, and compared to a standard CPA attack along with a template attack.