PRIVACY PRESERVATION TECHNIQUES FOR PERSONALIZED DATA IN BIG DATA

The recent advancements in this digital world huge amount of information are generated and shared, and the management of such large data is the most difficult and challenging task. Due to its size and variety of data, its name big data was derived. In the management of this data, some information may be disclosed. This type of disclosure can lead to leakage of Personal Identifiable Information (PII), as it contains individual’s information. The voluminous data generated from the various sources can be processed and analyzed to support decision making. However, data analytics is prone to privacy violations. Due to this, privacy has become one a major challenge of big data. There are different approaches to privacy preservation is processed like encryption based methodology, anonymization based method and noise based techniques in big data. Here the issues and methods are discussed and successfully analysed with privacy preservation and Big Data. This research paper examined various privacy threats, privacy preservation techniques and models with their limitations, and the analysis shows which one is the best method that guaranteed true privacy.