Privacy Preserving Data Mining Techniques by using a Data Anonymization - based Framework
Arti K. Pandya
, Priyanka R. Raval
mining; privacy preserving; sensitive attributes; privacy; privacy preserving techniques
Data mining techniques are used to mine the knowledge from a large database. But sometime these knowledge can disclose sensitive information about the data holder or individuals. The goal of privacy preservation technique is to release aggregate information about the data, without leaking individual information about participants. Several techniques of privacy preserving data mining have been proposed in literature. Privacy in data mining can be obtained by various techniques like Perturbation, Anonymization and Cryptographic. This paper tries to reiterate various Privacy Preserving Data Mining (PPDM) techniques based on anonymization currently developed to meet the privacy issues in the process of data mining.
"Privacy Preserving Data Mining Techniques by using a Data Anonymization - based Framework", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.2, Issue 4, page no.615 - 619, April-2017, Available :https://ijsdr.org/papers/IJSDR1704118.pdf
Volume 2
Issue 4,
April-2017
Pages : 615 - 619
Paper Reg. ID: IJSDR_170329
Published Paper Id: IJSDR1704118
Downloads: 000347182
Research Area: Engineering
Country: rajkot, Gujarat, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
