@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}
}