Title :
Privacy quantitative model with multiple decision factors
Author :
Gao, Feng ; He, Jingsha ; Ma, Shunan
Author_Institution :
Coll. of Comput. Sci. & Technol., Beijing Univ. of Technol., Beijing, China
Abstract :
In various computing environments and their applications, before any useful service offered, some user information which may contain privacy must be submitted. So how much privacy can the user afford to lose in order to get some service? It should be important to study effective privacy quantitative method in network environments. In this paper, we propose a novel privacy quantitative model with multiple decision factors. Our motivation is supply a privacy quantitative model, according to the result of quantification user can get the decision for their privacy disclosure. Our main contributions include following. (1) With multiple decision factors considered, our model satisfy privacy demand well, and support privacy disclosure decision more trustfully; (2) Allow the users set their privacy preference in the privacy quantitative model, and the users can change their privacy preference conveniently; (3) Our model can be used in various computing applications to protect privacy flexibly.
Keywords :
data privacy; decision theory; multiple decision factors; privacy disclosure decision; privacy preference; privacy quantitative model; Information entropy; information entropy; multiple decision factors; privacy quantitative;
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
DOI :
10.1109/ICICISYS.2010.5658672