Soft Analytical Side-Channel Attacks

In this paper, we introduce a new approach to side-channel key recovery, that combines the low time/memory complexity and noise tolerance of standard (divide and conquer) differential power analysis with the optimal data complexity of algebraic side-channel attacks. Our fundamental contribution for this purpose is to change the way of expressing the problem, from the system of equations used in algebraic attacks to a code, essentially inspired by low density parity check codes. We then show that such codes can be efficiently decoded, taking advantage of the sparsity of the information corresponding to intermediate variables in actual leakage traces. The resulting soft analytical side-channel attacks work under the same profiling assumptions as template attacks, and directly exploit the vectors of probabilities produced by these attacks. As a result, we bridge the gap between popular side-channel distinguishers based on simple statistical tests and previous approaches to analytical side-channel attacks that could only exploit hard information so far.