Title :
A review on privacy preserving data mining
Author :
Shanthi, A.S. ; Karthikeyan, Madurakavi
Author_Institution :
Tamilnadu Coll. of Eng., Coimbatore, India
Abstract :
The information is rich: but the knowledge is poor. To gain a better knowledge from available information, number of techniques and methods has been developed in the area of data mining so far. On the other hand privacy is one of the most important properties of information that any system should satisfy. The secrecy of the information must be maintained while sharing the information among different un-trusted parties. Thus privacy plays a major role and also an important issue in most of the data mining applications. Best suited Privacy Preserving Data Mining (PPDM) algorithm for different levels of mining which minimizes the information loss and improves accuracy of the mined data are identified based on this survey.
Keywords :
data mining; data privacy; information secrecy; information sharing; privacy preserving data mining; Anonymization; Data mining; Perturbed data; Privacy preserving; Randomization;
Conference_Titel :
Computational Intelligence & Computing Research (ICCIC), 2012 IEEE International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4673-1342-1
DOI :
10.1109/ICCIC.2012.6510302