Editor/Reviewer loginFrequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
IJCATR Volume 6 Issue 2
A Comprehensive Survey on Privacy Preserving Big Data Mining
S.Srijayanthi R.Sethukkarasi
10.7753/IJCATR0602.1002
keywords : big data; confidential; data mining; privacy preservation; sensitive
In recent years, privacy preservation of large scale datasets in big data applications such as physical, biological and biomedical sciences is becoming one of the major concerned issues for mining useful information from sensitive data. Preservation of privacy in data mining has ascended as an absolute prerequisite for exchanging confidential information in terms of data analysis, validation, and publishing. Privacy-Preserving Data Mining (PPDM) aids to mine information and reveals patterns from large dataset protecting private and sensitive data from being exposed. With the advent of varied technologies in data collection, storage and processing, numerous privacy preservation techniques have been developed. In this paper, we provide a review of the state-of-the-art methods for privacy preservation
@artical{s622017ijcatr06021002,
Title = "A Comprehensive Survey on Privacy Preserving Big Data Mining",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "6",
Issue ="2",
Pages ="79 - 86",
Year = "2017",
Authors ="S.Srijayanthi R.Sethukkarasi"}
The paper categorizes the privacy preservation techniques.
The various techniques of privacy preservation under each category are clearly specified.
The advantages and limitations of the techniques are specified.
The recent techniques for preserving privacy in big data mining are studied.