PEVLR: A New Privacy-Preserving and Efficient Approach for Vertical Logistic Regression.
Sihan MaoXiaolin ZhengJianguang ZhangXiaodong HuPublished in: ICONIP (4) (2023)
Keyphrases
- logistic regression
- privacy preserving
- privacy preserving data mining
- logistic regression models
- privacy preservation
- vertically partitioned data
- decision trees
- support vector
- private information
- multi party
- loss function
- horizontally partitioned data
- odds ratio
- privacy concerns
- privacy protection
- naive bayes
- privacy sensitive
- partitioned data
- data privacy
- sensitive information
- privacy requirements
- linear svm
- privacy issues
- private data
- secure multiparty computation
- data mining
- sensitive data
- privacy preserving association rule mining
- k nearest neighbor
- data perturbation
- preserving privacy