Securer and Faster Privacy-Preserving Distributed Machine Learning. (arXiv:2211.09353v1 [cs.CR])

With the development of machine learning, it is difficult for a single server
to process all the data. So machine learning tasks need to be spread across
multiple servers, turning centralized machine learning into a distributed one.
However, privacy remains an unsolved problem in distributed machine learning.
Multi-key homomorphic encryption over torus (MKTFHE) is one of the suitable
candidates to solve the problem. However, there may be security risks in the
decryption of MKTFHE and the most recent result about …

distributed machine machine learning privacy