Electric power CPS information attack identification method based on stack type self-encoding network model
A technology of stacked self-encoding and information attack, which is applied in the field of power CPS information attack identification based on stacked self-encoding network model, can solve the problems of low identification accuracy and complex data characteristics, and achieve improved convergence speed, strong applicability, and good effect
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[0041] A power CPS information attack identification method based on a stacked autoencoder network of the present invention will be described in detail below in conjunction with the accompanying drawings.
[0042] refer to figure 1 , a power CPS information attack identification method based on a stacked self-encoding network, comprising the following steps:
[0043] 1) Considering that the high-dimensional characteristics, nonlinear correlation and non-functional dependence in CPS data have caused serious obstacles in the process of research and application, the present invention proposes a maximum correlation minimum redundancy considering the improvement of the maximum information coefficient The attack feature selection method reflects the nonlinear correlation and non-functional dependence in the data features, and analyzes the correlation and redundancy between the features, and then selects the optimal attack feature set
[0044](a) Data preprocessing. CPS data may co...
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