Title :
A method of Enhanced t - Closeness for privacy protection
Author :
Song Yang ; Li Lijie ; Zhang Jianpei ; Yang Jing
Author_Institution :
Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
Abstract :
For t-Closeness which did not give a specific algorithm, and the semantic privacy can´t custom question, on the basis of model of t-Closeness and enhanced k-anonymity technology, Enhanced t-closeness privacy protection method is proposed in this paper, gives a semantic privacy degree measure and specific implementation of the algorithm. This article gives two specific algorithms: a top-down approach and a method based on the genetic classification. Using this method can enhance the ability of resistance similar to sexual assault, effectively prevent privacy leaks, and ensure the availability of the data quality.
Keywords :
data protection; genetic algorithms; pattern classification; data privacy protection; data quality; enhanced T-closeness method; enhanced k-anonymity technology; enhanced t-closeness privacy protection method; genetic classification; semantic privacy degree measure; top-down approach; Classification algorithms; Measurement; Semantics; Sociology; Statistics; (t, a)-closeness; privacy protection; t-closeness;
Conference_Titel :
Measurement, Information and Control (ICMIC), 2013 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4799-1390-9
DOI :
10.1109/MIC.2013.6758241