@Article{jbd.2019.08706, AUTHOR = {Danping Dong, Yue Wu, Lizhi Xiong, Zhihua Xia}, TITLE = {A Privacy Preserving Deep Linear Regression Scheme Based on Homomorphic Encryption}, JOURNAL = {Journal on Big Data}, VOLUME = {1}, YEAR = {2019}, NUMBER = {3}, PAGES = {145--150}, URL = {http://www.techscience.com/jbd/v1n3/38305}, ISSN = {2579-0056}, ABSTRACT = {This paper proposes a strategy for machine learning in the ciphertext domain. The data to be trained in the linear regression equation is encrypted by SHE homomorphic encryption, and then trained in the ciphertext domain. At the same time, it is guaranteed that the error of the training results between the ciphertext domain and the plaintext domain is in a controllable range. After the training, the ciphertext can be decrypted and restored to the original plaintext training data.}, DOI = {10.32604/jbd.2019.08706} }