Algorithm for Multidimensional K-anonymity by R Tree
Deng Jing-jing, Xiaojun Ye · Jisuanji gongcheng · 2008
K-anonymization is an important approach to protect data privacy in data publishing scenario.Like K-D tree for multidimensional K-anonymity,this paper proposes,an implementation of R tree in which each record is considered as a point in d-dimensional space of the attribute.Instead of dividing the region into pieces,the nearby rectangles are grouped into parent minimal bounding rectangles and forms disk blocks.Experiment results by modifying several parameters show that the algorithm can handle higher dimensionality compared with grid file or k-d tree.