Clustering-anonymity method for data-publishing privacy preservation

DOI

10.2991/icecee-15.2015.8How to use a DOI?

Keywords

Clustering-anonymity; privacy preservation; table data

Abstract

Data-publishing generally need to be treated by anonymity to protect its privacy information from disclosure. Existing anonymity methods have little distincation between different types of Quasi-identifiers in investigating generalization.Aimed to privacy preservation for pulblishing data from table, A clustering-anonymity data publishing method is proposed by using the ideas of clustering algorithm. The method makes generalization into Quasi-identifiers according to its different type, It gives the reasonable definition of the distance between one tuple and the other or one equvialance class; Dueing to partitioning cluster one by one controlled by the value of ,it achieves partition with the approximate same size of every equvialance class, So it reduces the amount of calculation of distances,and saves the running time accordingly.Experimental results verify the effectiveness of the method.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huowen Jiang
PY  - 2015/06
DA  - 2015/06
TI  - Clustering-anonymity method for data-publishing privacy preservation
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 34
EP  - 37
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.8
DO  - 10.2991/icecee-15.2015.8
ID  - Jiang2015/06
ER  -