The use of data combined with tailored statistical analysis have presented a unique opportunity to organizations in diverse elds to observe users' behaviors and needs, and accordingly adapt and ne tune their services. However, in order to oer utilizable, plausible and personalized alternatives to users, this process usually also entails a breach of their privacy. The use of statistical databases for releasing data analytics is growing exponentially, and while many cryptographic methods are

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... zed to protect the condentiality of the data a task that has been ably carried out by many authors over the years only a few works focus on the problem of privatizing the actual databases. Believing that securing and privatizing databases are two equilateral problems, in this paper we propose a hybrid approach by combining Functional Encryption with the principles of Dierential Privacy. Our main goal is not only to design a scheme for processing statistical data and releasing statistics in a privacy-preserving way but also provide a richer, more balanced and comprehensive approach in which data analytics and cryptography go hand in hand with a shift towards increased privacy.