BCP-based joint delegation learning model and protocol - Sheng GAO; Kang XIANG; Youliang TIAN; Weijie TAN; Tao FENG; Xiaoxue WU (Tongxin xuebao)
In order to realize data security sharing and reduce the computing costs of clients in data mining process, a joint delegation learning model and protocol based on BCP homomorphic encryption algorithm was proposed.Firstly, a privacy preserving method based on false records was proposed for the security of decision tree model.Secondly, in view of the vertical and horizontal distribution of data, the corresponding delegation learning protocols based on privacy preserving delegation dot product algorithm and privacy preserving delegation entropy algorithm was proposed.Finally, the security proof and the performance analysis of delegation learning protocols and decision tree model structure were given.The results show that the privacy protection method based on false records does not affect the final model construction, and the final model obtained by each client is the same as that constructed by real data.