The invention discloses a
side channel attack method based on a multi-
label and multi-expert network, and the method comprises the steps: firstly designing and constructing a three-dimensional multi-
label matrix based on a binary
label calculation method for a public
original data set of a target cryptographic
algorithm; secondly, designing a multi-expert
network model based on an attention mechanism, comprising an input layer, an expert
network layer, a sharing layer and an output layer, and realizing parallel
recovery of all key bytes of the target cryptographic
algorithm; and completing training through grid search, and finally completing
side channel attack by using the trained model. According to the method, parallel
recovery of all key bytes of the target cryptographic
algorithm is completed through one-
time model training, manual selection of interest point intervals is avoided,
side channel attack complexity is reduced, and
attack efficiency is improved; meanwhile, the learning ability of the model is improved through an attention mechanism, and the robustness of the model is improved through common learning of a sharing layer, so that the success rate of side channel attacks is improved.