Privacy by design in big data: An overview of privacy enhancing technologies in the era of big data analytics

The extensive collection and further processing of personal information in the context of big data analytics has given rise to serious privacy concerns, especially relating to wide scale electronic surveillance, profiling, and disclosure of private data. Despite the benefits of analytics, it cannot be accepted that big data comes at a cost for privacy. At the same time technology and innovation cannot be stopped. It is, thus, of utmost importance to craft the right balance between making use of big data technologies and protecting individuals’ privacy and personal data.
ENISA publishes a report on privacy by design in big data, focusing exactly on striving this balance by highlighting privacy as a core value of big data and examining how technology can be on its side.    
In particular, following ENISA’s former work on privacy and data protection by design, this report aims at contributing to the big data discussions by defining privacy by design strategies and relevant privacy enhancing technologies, which can allow for all the benefits of analytics without compromising the protection of personal data. Such technologies include anonymization, the “traditional” analytics technique, the emerging area of encrypted search and privacy preserving computations, granular access control mechanisms, as well as policy enforcement and accountability. Moreover, new transparency and access tools in big data are explored, together with techniques for user empowerment and control.
 
For full report
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