Privacy-Preserving Distributed Machine Learning via Local Randomization and ADMM Perturbation.
Xin WangHideaki IshiiLinkang DuPeng ChengJiming ChenPublished in: IEEE Trans. Signal Process. (2020)
Keyphrases
- privacy preserving
- machine learning
- data perturbation
- horizontally partitioned data
- horizontally partitioned
- multi party
- privacy preserving data mining
- partitioned data
- distributed data mining
- privacy sensitive
- privacy guarantees
- vertically partitioned data
- privacy preservation
- secure multiparty computation
- privacy preserving association rule mining
- private information
- privacy preserving classification
- privacy protection
- sensitive information
- data privacy
- privacy concerns
- preserving privacy
- scalar product
- personal data
- differential privacy
- decision trees
- naive bayesian classification
- distributed systems
- data publishing
- distributed environment
- sensitive data
- data mining
- distributed computing
- private data
- databases
- distributed data
- peer to peer
- privacy requirements