Title :
Privacy-Preserving Data Imputation
Author :
Jagannathan, Geetha ; Wright, Rebecca N.
Author_Institution :
Stevens Inst. of Technol., Hoboken, NJ
Abstract :
In this paper, we investigate privacy-preserving data imputation on distributed databases. We present a privacy-preserving protocol for filling in missing values using a lazy decision tree imputation algorithm for data that is horizontally partitioned between two parties. The participants of the protocol learn only the imputed values; the computed decision tree is not learned by either party
Keywords :
data privacy; decision trees; distributed databases; protocols; data imputation; distributed databases; lazy decision tree; privacy preservation; Classification tree analysis; Cleaning; Data mining; Data privacy; Decision trees; Distributed databases; Entropy; Filling; Partitioning algorithms; Protocols;
Conference_Titel :
Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2702-7
DOI :
10.1109/ICDMW.2006.134
