A Dataset Generation Framework for profiling Disassembly attacks using Side-Channel Leakages and Deep Neural Networks. (arXiv:2207.12068v2 [cs.CR] UPDATED)

Various studies among side-channel attacks have tried to extract information
through leakages from electronic devices to reach the instruction flow of some
appliances. However, previous methods highly depend on the resolution of traced
data. Obtaining low-noise traces is not always feasible in real attack
scenarios. This study proposes two deep models to extract low and high-level
features from side-channel traces and classify them to related instructions. We
aim to evaluate the accuracy of a side-channel attack on low-resolution data
with …

attacks channel framework networks neural networks profiling side-channel