Using Noise Addition Method Based on Pre-mining to Protect Healthcare Privacy
- Authors
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Likun Liu
College of Computer Science and Technology, Jilin University, Changchun, P. R. China
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Kexin Yang
College of Computer Science and Technology, Jilin University, Changchun, P. R. China
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Liang Hu
Jilin Economic vocational and Technical College, Changchun, P. R. China
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Lina Li
Jilin Economic vocational and Technical College, Changchun, P. R. China
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- Abstract
- With medical device cyber-physical systems being more and more widely used, a lot of healthcare data are produced, making data sharing for health research a vital requirement. But, privacy concerns must be addressed before sharing and publishing any data set. Privacy-preserving data mining (PPDM) is an important technology to protect personal privacy. This paper begins with a proposal of two new noise addition algorithms for perturbing the original healthcare data, and then applies them to a two-step perturbation model. Experiments show that the algorithms given in this paper have much higher accuracy than existing ones under the similar privacy strength.
- References
- Downloads
- Published
- 2012-06-29
- Issue
- Vol. 14 No. 2 (2012)
- Section
- Articles