Big Data is increasingly being used in many sectors. Research institutions, Industry and government agencies active in Big Data technologies, have been working more than ever on building novel data analysis techniques. Business players and technology providers work on creating new products and services and even developing entirely new business models that are massively based on aggregation and analysis, of extremely large and fast growing volumes of data.

Experience has shown that Big Data applications can provide a dramatic increase in the efficiency and effectiveness of decision-making in complex organizations and communities. However, besides its benefits or in some cases because of them, Big Data also bears a number of security risks. Big Data systems are increasingly becoming attack targets by threat agents, and more and more elaborate and specialized attacks will be devised to exploit vulnerabilities and weaknesses.

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. In order to allow for all the benefits of analytics without invading individuals’ private sphere, it is of utmost importance to draw the limits of Big Data processing and integrate the appropriate data protection safeguards in the core of the analytics value chain.

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