Whereas, in traditional public-key encryption, decryption is an all-or-nothing affair (i.e., a receiver is either able to recover the entire message using its key, or nothing), functional encryption enables fine-grained access control and computation on encrypted data, as required to protect data in the cloud.<br/> In the first part of the talk, we provide an introduction to functional encryption and an overview of its impact on the field of cryptography. In the second part, we propose a simple functional encryption scheme for the inner-product functionality that despite its simplicity can be successfully used in the context of descriptive statistics. The security of the scheme can be based on the Decisional Diffie–Hellman or the Learning with Errors assumption offering a trade-offs in terms of expressiveness and efficiency.