SecretFlow-SPU: A Performant and User-Friendly Framework for Privacy-Preserving Machine Learning.
Junming MaYancheng ZhengJun FengDerun ZhaoHaoqi WuWenjing FangJin TanChaofan YuBenyu ZhangLei WangPublished in: USENIX Annual Technical Conference (2023)
Keyphrases
- user friendly
- privacy preserving
- machine learning
- multi party
- privacy preserving data mining
- privacy preservation
- data mining
- privacy preserving data mining algorithms
- user interface
- privacy guarantees
- artificial intelligence
- sensitive information
- data privacy
- privacy sensitive
- graphical interface
- partitioned data
- private information
- expert systems
- knowledge discovery
- privacy preserving association rule mining
- homomorphic encryption
- vertically partitioned data
- user friendly interface
- data perturbation
- private data
- knowledge base
- privacy concerns
- privacy protection