An efficient heuristic power analysis framework based on hill-climbing algorithm

Traditional nonprofiling side-channel analysis frequently adopts divide-and-conquer strategy to recover the secret key of a cryptographic algorithm. Only a single key byte is used, whereas the remaining bytes are considered extraneous noise. If the cryptographic algorithm is implemented in hardware with parallel processing, the strategy will lead to the inefficient use of information. The combination of intelligent algorithms and side-channel analysis offers a different idea for nonprofiling methods for parallel hardware implementations. It transforms the problem of key recovery into key optimization. In this paper, we adopt this idea and propose an efficient heuristic framework to assist correlation power analysis. The multipoint hill-climbing algorithm will be used to find the optimal key candidates with higher scores, and the correct key will be found in the optimal key candidates by key enumeration. Multiple bytes of the secret key are used to take full advantage of the helpful information. Besides, two search strategies are introduced to overcome the efficiency problem, and two key enumeration strategies are introduced to solve the key recovery problem when the traces are insufficient. Experimental results on the public DPA Contest V1 dataset show that the heuristic framework performs better than other classical methods, verifying its effectiveness.