Data-driven evolutionary optimization has witnessed great success in solving complex real-world problems. However, existing data-driven algorithms require that all data are centrally stored, which is not always practical and may be vulnerable to privacy leakage security threats if the must collected from different devices. To address above issue, this paper proposes a federated framework able p...