Research Article
Privacy-preserving Technology and Its Applications in Statistics Measurements
@INPROCEEDINGS{10.4108/infoscale.2007.211, author={Yifei Yao and Liusheng Huang and Wei Yang and Yonglong Luo and Weiwei Jing and Weijiang Xu}, title={Privacy-preserving Technology and Its Applications in Statistics Measurements}, proceedings={2nd International ICST Conference on Scalable Information Systems}, proceedings_a={INFOSCALE}, year={2010}, month={5}, keywords={secure multi-party computation (SMC) privacy-preserving statistics measurements commutative encryption data perturbation.}, doi={10.4108/infoscale.2007.211} }
- Yifei Yao
Liusheng Huang
Wei Yang
Yonglong Luo
Weiwei Jing
Weijiang Xu
Year: 2010
Privacy-preserving Technology and Its Applications in Statistics Measurements
INFOSCALE
ICST
DOI: 10.4108/infoscale.2007.211
Abstract
Statistics measurements are of great importance in data set description. Although there have been some papers about statistical analysis, little work focused on the flavors of measurements or privacy-preserving property. In this paper, we consider the applications of secure multi-party computation technology in statistics measurements computation to preserve privacy. Secure protocols of harmonic mean, geometric mean and mode are proposed. Detailed analyses about security and complexity of them are also presented.
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