Privacy Preserving Data Mining: Approaches, Applications And Research Directions

Abstract

Large amount of data is generated nowadays from different fields and domains such as healthcare, retail, finance, social media etc. Data mining is used to extract and discover information or knowledge from this data. Important results can be obtained through mining process but it can lead to disclosure of sensitive data which has to be protected. Mining which allows useful knowledge to be discovered while preserving the privacy of an individual is Privacy Preserving Data Mining (PPDM). In this paper, role and scheme of Privacy Preserving Data mining is discussed with the help of different approaches to it. Application domains in which privacy is necessary are surveyed. Also, existing techniques of PPDM given by different authors are presented. Research findings are described in conclusion part of the paper to guide further research in this area.

Keywords: Privacy preserving, Data Mining, Anonymisation, Randomisation, Cryptography, Perturbation, Condensation