Study on Privacy Preserving Clustering Process in Big Data
Protecting Individual Privacy in Data Mining Analysis
Keywords:
privacy preserving, clustering process, big data, anonymization, computational cost, data mining, individual data, analysis, research, private dataAbstract
In privacy preserving data mining, two principle approaches have been talked about in the writing viz. Cryptographic 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 cryptographic 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.Published
2017-04-01
How to Cite
[1]
“Study on Privacy Preserving Clustering Process in Big Data: Protecting Individual Privacy in Data Mining Analysis”, JASRAE, vol. 13, no. 1, pp. 1009–1014, Apr. 2017, Accessed: Jul. 25, 2025. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/6673
Issue
Section
Articles
How to Cite
[1]
“Study on Privacy Preserving Clustering Process in Big Data: Protecting Individual Privacy in Data Mining Analysis”, JASRAE, vol. 13, no. 1, pp. 1009–1014, Apr. 2017, Accessed: Jul. 25, 2025. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/6673