Privacy preserving clustering algorithm of limiting privacy breaches
Zou Han-bin · Jisuanji gongcheng yu sheji · 2010
To deal with privacy breaches in the extreme cases of data mining,the theory that the privacy breaches could have avoided are analyzed,when the Laplace noise are added to the data clustering.Combining the methods of the principal analysis and the Laplace noise,a privacy preserving clustering algorithm of limiting privacy breaches is proposed.The algorithm got rid of the relevance of the data to use principal component analysis,and the distance of the disturbance chance is calculated after added Laplace noise into the main component of the data vector,those made the disturbed data not recover and played a part in the limiting privacy breaches in the privacy preserving clustering algorithm.Results of the simulation experiment indicated the proposed algorithm for limiting privacy breaches in the data clustering is correct and effective.