This paper introduces a general framework for supporting data-driven privacy-preserving big
data management in distributed environments, such as emerging Cloud settings. The …

Starting from our previous research where we in-troduced a general framework for
supporting data-driven privacy-preserving big data management in distributed …

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 …

OLAP is an authoritative analytical tool in the emerging big data analytics context, with
particular regards to the target distributed environments (eg, Clouds). Here, privacy …

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 …

Big data has become a great asset for many organizations, promising improved operations
and new business opportunities. However, big data has increased access to sensitive …

Big data, because it can mine new knowledge for economic growth and technical
innovation, has recently received considerable attention, and many research efforts have …

Along with the ever increasing growth in data collection and its mining, there is an
increasing fear of compromising individual and population privacy. Several techniques have …

In recent years, big data have become a hot research topic. The increasing amount of big
data also increases the chance of breaching the privacy of individuals. Since big data …

Machine learning has played an increasing important role in big data systems due to its
capability of efficiently discovering valuable knowledge and hidden information. Often times …