Published Paper Details:

Improbable quantities of data is being produced by various organizations like hospitals, banks, e-commerce, retail and supply chain, etc. by virtue of digital technology. Not only individuals but machines also subsidize to data in the form of closed circuit television streaming, web site logs, etc. Tons of data is produced every minute by social media and smart phones. Big data is a word used for very large data sets that have more diverse and composite structure. These features usually correlate with additional problems in storing, analyzing and applying further procedures or mining results. This paper covers uses of privacy by taking existing methods such as k-anonymity, T-closeness and L-diversity and its implementation in business. There have been a various privacy-preserving mechanisms developed for privacy protection at different stages. Although data analytics is useful in decision making, it will lead to serious privacy apprehensions. Hence privacy preserving data analytics became very important. The goal of this paper is to deliver a major review of the privacy preservation mechanisms in big data and present the challenges for existing mechanisms and paper also examines various privacy threats with their limitations in unstructured data.