Privacy preserving method based on GM(1,1) and its application to clustering

The purpose of this paper is to provide a privacy preserving method based on grey model and apply it to clustering, so that the privacy of the individuals can be protected while the information loss is kept low.

GM(1,1) model is utilized reversely in the approach to add noise to the original data, so as to make use of the grey information to blur the true one.

It is shown that the privacy preserving method based on grey model can achieve both high effectiveness and high efficiency.

The paper presents the first attempt to apply the grey model to protect data privacy. The experimental results show the effectiveness and the efficiency of the proposed method.