## Reference [1]. Jakub Konen, H. Brendan McMahan, Daniel Ramage, Peter Richtik. **Federated Optimization: Distributed Machine Learning for On-Device Intelligence.** 2016 [2]. H. Brendan McMahan, Eider Moore, Daniel Ramage, Blaise Agera y Arcas. **Federated Learning of Deep Networks using Model Averaging.** 2017 [3]. Jakub Konen, H. Brendan McMahan, Felix X. Yu, Peter Richtik, Ananda Theertha Suresh, Davepen Bacon. **Federated Learning: Strategies for Improving Communication Efficiency.** 2016 [4]. Qiang Yang, Yang Liu, Tianjian Chen, Yongxin Tong. **Federated Machine Learning: Concept and Applications.** 2019 [5]. Kai He, Liu Yang, Jue Hong, Jinghua Jiang, Jieming Wu, Xu Dong et al. **PrivC - A framework for efficient Secure Two-Party Computation. In Proceedings of 15th EAI International Conference on Security and Privacy in Communication Networks.** SecureComm 2019 [6]. Mart Abadi, Andy Chu, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, Li Zhang. **Deep Learning with Differential Privacy.** 2016 [7]. Virginia Smith, Chao-Kai Chiang, Maziar Sanjabi, Ameet Talwalkar. **Federated Multi-Task Learning** 2016 [8]. Yang Liu, Tianjian Chen, Qiang Yang. **Secure Federated Transfer Learning.** 2018