DocumentCode :
584816
Title :
Shearing based data transformation approach for privacy preserving clustering
Author :
Manikandan, G. ; Sairam, N. ; Sudhan, R. ; Vaishnavi, B.
Author_Institution :
Sch. of Comput., SASTRA Univ., Thanjavur, India
fYear :
2012
fDate :
26-28 July 2012
Firstpage :
1
Lastpage :
5
Abstract :
Data mining is a technique used to extract un-known patterns from large volume of data. Privacy has be-come a major concern in data mining. The data which are stored in the organization´s database may have some confi-dential information and hence it has to be protected from any unauthorized usage. In order to overcome the privacy problem in this paper we propose a new technique called shearing based composite transformation. Data owner trans-forms the original data into distorted data by shearing based composite data transformation. Only this distorted data is given to the clients. For clustering we have used k-means algorithm and from our experiments we found that the total number of elements in the clusters is same with the original and distorted data.
Keywords :
authorisation; data mining; data privacy; pattern clustering; data mining; data owner; distorted data; k-means algorithm; privacy preserving clustering; shearing based composite transformation; shearing based data transformation approach; unauthorized usage; Clustering algorithms; Computers; Data mining; Educational institutions; Ethics; Privacy; Random access memory; Privacy preserving; clustering; composite data transformations; shearing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing Communication & Networking Technologies (ICCCNT), 2012 Third International Conference on
Conference_Location :
Coimbatore
Type :
conf
DOI :
10.1109/ICCCNT.2012.6395985
Filename :
6395985
Link To Document :
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