A side-channel based disassembler for the ARM-Cortex M0.

The most common application for side-channel attacks is the extraction of secret information, such as key material, from the implementation of a cryptographic algorithm. However, using side-channel information, we can extract other types of information related to the internal state of a computing device, such as the instructions executed and the content of registers. We used machine learning to build a side channel disassembler for the ARM-Cortex M0 architecture, which can extract the executed instructions from the power traces of the device. Our disassembler achieves a success rate of 99% under ideal conditions and 88.2% under realistic conditions when distinguishing between groups of instructions. We also provide an overview of the lessons learned in relation to data preparation and noise minimization techniques.