Title :
Privacy Preserving Clustering by Random Response Method of Geometric Transformation
Author :
Liu, Jie ; Xu, Yifeng
Author_Institution :
Coll. of Comput. Sci. & Technoledge, Harbin Eng. Univ., Harbin, China
Abstract :
With the large influx of the data mining technology and mining tools, the confidentiality requirements of the personal privacy are becoming more and more urgent. Therefore, how to ensure personal privacy and get the correct mining results becomes a severe issue to be resolved. In this paper, we propose a kind of random response method of geometric transformation- the combination of the random response technology and the geometric transform algorithm. The algorithm is designed to solve the shortage of low privacy protection of the geometric transform algorithm. The algorithm first gives four parameters, corresponding to the probability of four different types of geometric transformations. According to the various random number generated, different geometric transformation method is selected, which serves the dual effect of privacy protection. Our experiment proves that this method has a high degree of privacy protection and can get correct mining results.
Keywords :
data mining; data privacy; pattern clustering; probability; random processes; confidentiality requirements; data mining technology; geometric transform algorithm; geometric transformation; low privacy protection; mining tools; personal privacy; privacy preserving clustering; probability; random response method; Association rules; Clustering algorithms; Data analysis; Data engineering; Data mining; Data privacy; Euclidean distance; Perturbation methods; Probability distribution; Protection;
Conference_Titel :
Internet Computing for Science and Engineering (ICICSE), 2009 Fourth International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-6754-9
DOI :
10.1109/ICICSE.2009.31