privacy issues in big data analytics


Is there a contradiction between privacy and security in big data?

    However, there is an obvious contradiction between the security and privacy of big data and the wide- spread use of big data. This paper focuses on privacy and security concerns in big data, differentiates between privacy and security and privacy requirements in big data.

What is big data analytics?

    Big data analytics is the term used to describe the process of researching massive amounts of complex data in order to reveal hidden patterns or identify secret correlations. However, there is an obvious contradiction between the security and privacy of big data and the wide- spread use of big data.

Is de-identification feasible for privacy-preserving big data analytics?

    • De-identification is more feasible for privacy-preserving big data analytics if develop efficient privacy-preserving algorithms to help mitigate the risk of re-identification. There are three -privacy-preserving methods of De-identification, namely, K-anonym- ity, L-diversity and T-closeness.

What is a common theme of big data?

    A common theme of big data is that the data are diverse, i.e., they may contain text, audio, image, or video etc. This differing qualities of data is signified by variety. In order to ensure big data privacy, various mechanisms have been developed in recent years.
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