Privacy preserving computation protocol for data analytics

A privacy preserving computation protocol for data analytics is described. The protocol includes a method for privacy-preserving computation of aggregated private data of a group of client devices wherein the method comprises: a server selecting at least t client devices from the group of client devices, each client device in the group: being identifiable by client index i; comprising an encryption function; being provided with key information including an encryption key e and a decryption key of a homomorphic threshold cryptosystem; generating or being provided with an random value r i and having access to or being provided with the random values of the other client devices in the group; the server transmitting client information to each selected client device, the client information including client indices identifying the selected client devices, the client information signalling a client device that the server would like aggregate encrypted private data of each of the selected client devices; the server receiving randomized encrypted private data and an associated decryption share from each selected client device, the decryption shares being configured such that decryption key d can be reconstructed on the basis of t decryption shares; and, the server aggregating, preferably summing or adding, the received randomized encrypted private data of the selected client devices using the homomorphic properties of the cryptosystem and using the decryption shares for decrypting the aggregated randomized encrypted private data into cleartext.