Side Channel Cryptanalysis with Hidden Markov Models
ABSTRACT:
This talk looks at how Hidden Markov Models can be applied to side-channel cryptanalysis. In particular, we look at how they can help overcome software counter-measures to side-channel cryptanalysis as well as noisy side-channel data. After introducing the basic principles of side-channel cryptanalysis, we examine the methodology of Karlof and Wagner. We finish with a description of recent work in this area which does not rely on the side-channel data being tokenized ahead of time and provides a more realistic error model for noisy side-channels that allows a wider variety of error types, including incomplete side-channel traces.
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