A General Overview of Privacy-Preserving Big Data Management and Analytics Models, Methods and Techniques in Specific Domains: Static and Dynamic Distributed Environments

Abstract

Privacy-preserving big data management and analytics is gaining the momentum within the research community, and several current research efforts aim to provide solutions to the challenges that emerge when models, techniques and algorithms must be delivered on top of massive, distributed big data repositories, especially with regards to emerging distributed settings such as Clouds and social networks. In this paper, at the convergence of the contexts of static and dynamic distributed environments, we provide a general overview of models, issues and approaches, along with some reference frameworks. Indeed, both static and dynamic distributed environments are relevant cases of settings where the privacy of big data turns to be critical. Finally, we discuss emerging research directions.