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Privacy Preserving Techniques on Centralized, Distributed and Social Network Data – A Review
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 140 - Number 8 |
| Year of Publication: 2016 |
| Authors: R. Padmaja, V. Santhi |
10.5120/ijca2016909430
|
R. Padmaja, V. Santhi . Privacy Preserving Techniques on Centralized, Distributed and Social Network Data – A Review. International Journal of Computer Applications. 140, 8 ( April 2016), 48-52. DOI=10.5120/ijca2016909430
Abstract
Privacy Preserving Data Publishing refers publishing data in such a way that the privacy of the individuals are preserved. The Published data can further be used for various Data Analysis and Data Mining tasks. Techniques used to preserve privacy of individuals before publishing is called Anonymization Techniques. Initially only centralized data need to be published for analysis and Mining. Later with the advent of Internet, it has become necessary to publish Distributed and Social network data. The Anonymization Techniques that are applied on Centralized data can be applied on both Distributed and Social Network data with little modifications. This Paper is to present a brief review of Anonymization Techniques like k-anonymity and l-diversity on Centralized, Distributed and Social Network Data.
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