Method for collaborative machine learning

An apparatus comprising at least one training unit for one or more data owners collaborating to a system for storing private data and at least one encrypted model, said training unit being implemented as a trusted execution environment;

• said training unit being configured to communicate with at least one aggregator unit of the system;
• wherein the communication between the at least one training unit and the at least one aggregator unit is encrypted;
• and wherein at least one administration unit is configured to receive model gradients from the at least one training unit, generate masks for the gradients of each of the at least one training unit such that the sum of the masks equals to a predefined noise level, and transmit the masks to at least one corresponding unit of the at least one training unit;
• said at least one administration unit being configured for controlling communication and synchronization between the at least one training unit and the at least one aggregator, and said at least one administration unit being implemented in the trusted executed environment.