Sensitive Information Protection Method for Clustering Mining Based on Isometric Transformation
Bei Hua · Jisuanji gongcheng · 2011
To solve the disadvantage of classic Rotation-based Transformation(RBT) algorithm which is ineffective of quantification security degree that has to be preliminary set up,a method of selecting randomly isometric transformation angles is presented.This method randomly selects the security degree in a reasonable range of data set.It can insure that the spatial distance for any two points in the new data set is the same as in the raw data set after the raw data set is transformed into the new data set.The theoretical analysis and experimental results show that,the presented algorithm is simple and easy to implement.And the transformation of the data is random every time and the new data set is obviously different from the raw data set.The attacker can not trace the original data sets,and it can preserve the private information.