Review of K-means Algorithm Optimization Based on Differential Privacy

Abstract

Differential privacy K-means algorithm (DP K-means),as a kind of privacy preserving data mining (PPDM) model based on differential privacy technology,has attracted much attention from researchers because of its simplicity,efficiency and ability to guarantee data privacy.Firstly,the principle and privacy attack model of differential privacy K-means Algorithm are described,and the shortcomings of the algorithm are analyzed.Then,the advantages and disadvantages of the improvement research of DP K-means algorithm are discussed and analyzed from three perspectives,including data preprocessing,privacy budget allocation and cluster partition,and the relevant data sets and common evaluation indexes in the research are summarized.At last,the challenging problems to be solved in the improvement research of DP K-means algorithm are pointed out,and the future development trend of DP K-means algorithm is prospected.

Keywords

• differential privacy k-means algorithm|differential privacy|privacy preservation|privacy preserving data mining