Privacy-preserving big data analytics a comprehensive survey.

In this paper, we present a comprehensive survey of privacy-preserving big data analytics. We introduce well-designed taxonomies which offer both systematic views and a detailed classification of this challenging research field. We give insights into recent studies on existing active topics in the field. Furthermore, we identify open future research directions for privacy-preserving big data analytics. This survey can serve as a good reference source for the development of modern privacy-preserving techniques to address various privacy-related scenarios to be encountered in practice. • A comprehensive survey of privacy-preserving big data analytics. • Well-designed taxonomies with both systematic views and detailed classification. • Insights into recent works on existing active privacy topics in social networks. • Open future research directions for privacy-preserving big data analytics. • A good reference source to address various privacy-related scenarios. [ABSTRACT FROM AUTHOR]