The server is under maintenance between 08:00 to 12:00 (GMT+08:00), and please visit later.
We apologize for any inconvenience caused
Login  | Sign Up  |  Oriprobe Inc. Feed
China/Asia On Demand
Journal Articles
Laws/Policies/Regulations
Companies/Products
A Privacy Preservation Method for High Dimensional Data Mining
Author(s): 
Pages: 2187-2192
Year: Issue:  11
Journal: Acta Electronica Sinica

Keyword:  privacy preservationhigh dimensional data mininghash techniquerandom projectionsecure subspace;
Abstract: This paper proposes a privacy preservation method based on random projection to overcome the curse of dimen-sionality in privacy preserving data mining .To prevent leaks of random matrix which can lead to the reconstruction attack ,it first proposes the concepts of secure subspace and secure subspace mapping .Then ,it constructs a secure subspace mapping using hash technique ,which is implemented by a random projection matrix ,and it achieves a low distortion embedding while preserving the data privacy .Finally ,it proves that the secure subspace can preserve the Euclidean distance and inner product between any two original points .The experimental results show that the proposed technique can ensure the data quality in different data mining applications ef-fectively under the precondition of preserving data privacy .
Related Articles
loading...