A Model on Distributed Privacy Preserving Linear Regression Analysis Based on Homomorphic Encryption

Linear regression is one of the important methods of statistical analysis, but the research on linear regression analysis with privacy preserving for multiple data source in distributed environment is relatively less. To solve this problem, by using additive homomorphic encryption, a model on collaborative linear regression analysis with privacy preserving in non-trusted distributed environment is presented. The model makes full use of the calculating ability of distributed environment, the clients and statistical server collaboratively calculate linear regression parameters, and the sensitive data of each data source are protected in analysis process. Finally, the security of model is discussed in Semi- Honest Mode, and the performance of model is tested.