Optimization of multi-dimensional decomposition and plus noise algorithm in intelligent grid privacy protection
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Abstract:
To address the security problem of user privacy leak in the data acquisition and monitoring of smart grid, noise is usually added to achieve privacy protection. In this paper, a Laplacian noise algorithm based on multidimensional decomposition(MDLN) is proposed. The algorithm decomposes the original measured value into multidimensional data, and adaptively determines the Laplacian noise amplitude to be added according to the sensitivity of each dimension, achieving differential privacy by effective noise perturbation. The simulation results show that the MDLN algorithm has higher privacy protection and higher performance compared with the SLN(simple Laplacian noise algorithm) algorithm and ULN(uniform Laplacian noise algorithm) algorithm.
