Title : 
The state of the art and tendency of privacy preserving data mining
         
        
            Author : 
Wang, Bo ; Yang, Jing
         
        
            Author_Institution : 
College of Computer Science and Technology, Harbin Engineering University, Harbin, China
         
        
        
        
        
            Abstract : 
As a new branch of data mining, privacy preserving data mining has become more and more important in the information security field. This paper first presents an insight into the principles of privacy preserving data mining, and then marks out the difference with normal data mining through three stages, including single data record methods, centralized dataset mining technology and secure multiparty computation problem. By studying and analyzing privacy preserving data mining methods, the present problems and directions for future research are discussed.
         
        
            Keywords : 
Association rules; Classification algorithms; Data privacy; Databases; Decision trees; Privacy; centralized dataset mining; data mining; privacy preserving; secure multiparty computation; single data record;
         
        
        
        
            Conference_Titel : 
E -Business and E -Government (ICEE), 2011 International Conference on
         
        
            Conference_Location : 
Shanghai, China
         
        
            Print_ISBN : 
978-1-4244-8691-5
         
        
        
            DOI : 
10.1109/ICEBEG.2011.5881884