Title :
Privacy preserving based on association rule mining
Author :
Ma, Tinghuai ; Wang, Sainan ; Liu, Zhong
Author_Institution :
Sch. of Comput. & Software, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
Abstract :
Privacy has become an important issue in Data Mining. Many methods have been brought out to solve this problem. This paper deals with the problem of association rule mining which preserves the confidentiality of each database. In order to find the association rule, each participant has to share their own data. Thus, much privacy information may be broadcast or been illegal used. These issues can be divided into two categories: data hiding and knowledge hiding. This paper reviews the major method of privacy preserving on each category and choose some of them to complete our system. At the end, an improvement of sensitive rules hiding is proposed to make it more accuracy and security.
Keywords :
data mining; data privacy; association rule mining; data hiding category; data mining; knowledge hiding category; privacy preserving method; sensitive rules hiding; Book reviews; Cryptography; Itemsets; Variable speed drives; Association-rule; data hinding; data mining; knowledge hiding; privacy preserving;
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6539-2
DOI :
10.1109/ICACTE.2010.5578938