Study On Privacy Preserving Clustering Process In Big Data

Abstract

In privacy preserving data mining, two principle approaches have been talked about in the writing viz. Cryptography approaches and anonymization approaches. Be that as it may, our spotlight in this thesis is on the anonymization based approaches attributable to the lesser computational cost contrasted with the cryptography approaches. As of late, different associations in various divisions viz. Medicinal, Banking and Insurance gather, store and utilize individual data of their clients. Such gathered data are additionally utilized for the investigation and research purposes. To do likewise, data mining systems have been used for playing out the errand of examination and research work. In any case, the gathered data may contain individual explicit private data. In this way, breaking down such gathered data can uncover the private data of a person. Therefore, ensuring the private data of an individual turns into a prime research issue in privacy preserving data mining.