Footnote:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments September 12, 2020 erstellt
Description:
In today's technology centric world, data volume is increasing exponentially from embedded devices (mobile phones, automobiles, and sensor data). Individual engagement with the Internet has caused tremendous data growth through e-commerce portals, e-governance, and various social media networks. This data growth brings potential benefits that are significant and useful, and some initial success is achieved from a technological perspective to handle such voluminous amount of data. Along with benefits, it brings many challenges with respect to the data including storage, data exchange, curation, transportation, analysis, visualization, information in the form of analytics and privacy. When it is readily accepted that privacy of data itself is very important, the privacy of data analytics based information should also be very crucial. Hence this research would like to explore the important topic of preserving the privacy of information which has been generated through big data analytics. This paper commences with the investigations on various forms of data privacy threats, including disclosure, monitoring, identification, and discrimination; etc. and analyze the availability of various privacy-preserving techniques that are available for big data platforms. Further we would like to identify their limitations, and discuss the future course of action towards achieving privacy in big data analytics