Adaptive Differentially Quantized Subspace Perturbation (ADQSP): A Unified Framework for Privacy-Preserving Distributed Average Consensus.
Qiongxiu LiJaron Skovsted GundersenMilan Lopuhaä-ZwakenbergRichard HeusdensPublished in: IEEE Trans. Inf. Forensics Secur. (2024)
Keyphrases
- privacy preserving
- horizontally partitioned data
- multi party
- data perturbation
- horizontally partitioned
- partitioned data
- distributed data mining
- privacy sensitive
- privacy guarantees
- privacy preserving data mining
- vertically partitioned data
- privacy preservation
- secure multiparty computation
- privacy preserving classification
- private information
- distributed systems
- sensitive data
- data privacy
- private data
- sensitive information
- privacy concerns
- feature space
- preserving privacy
- medical data
- principal component analysis
- feature extraction
- naive bayesian classification
- privacy preserving association rule mining
- data publishing
- privacy issues
- high dimensional data
- privacy protection
- user privacy
- dimensionality reduction
- data sets
- record linkage
- face recognition
- communication cost
- database systems