Title :
A survey on privacy preserving data mining
Author :
Saranya, K. ; Premalatha, K. ; Rajasekar, S.S.
Author_Institution :
Anna Univ., Chennai, India
Abstract :
The field of privacy pursues rapid advances in recent years because of the increases in the ability to store data. One of the most important topics in research community is Privacy preserving data mining (PPDM). Privacy preserving data mining has become increasingly popular because it allows sharing of privacy sensitive data for analysis purposes. People today have become well aware of the privacy intrusions of their sensitive data and are very reluctant to share their information. The major area of concern is that non-sensitive data even may deliver sensitive information, including personal information, facts or patterns. This paper provides a wide survey of different privacy preserving data mining algorithms and analyses the representative techniques for privacy preserving data mining, and points out their merits and demerits.
Keywords :
data mining; data privacy; security of data; PPDM; data storage; knowledge extraction; knowledge mining; personal information; privacy preserving data mining algorithms; privacy sensitive data sharing; sensitive information delivery; Association rules; Conferences; Data privacy; Databases; Diseases; Privacy; data mining; privacy; privacy preserving; privacy preserving techniques; sensitive attributes;
Conference_Titel :
Electronics and Communication Systems (ICECS), 2015 2nd International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-7224-1
DOI :
10.1109/ECS.2015.7124885