SafeML: A Privacy-Preserving Byzantine-Robust Framework for Distributed Machine Learning Training.
Meghdad MirabiRené Klaus NikielCarsten BinnigPublished in: ICDM (Workshops) (2023)
Keyphrases
- privacy preserving
- machine learning
- multi party
- partitioned data
- privacy sensitive
- horizontally partitioned
- fault tolerant
- data privacy
- privacy preservation
- privacy preserving data mining algorithms
- horizontally partitioned data
- privacy guarantees
- privacy preserving data mining
- distributed systems
- data mining
- data sets
- distributed data mining
- data publishing
- sensitive data
- vertically partitioned data
- data analysis
- feature selection
- record linkage
- preserving privacy
- secure multiparty computation
- distributed environment
- privacy preserving association rule mining
- provide efficient solutions