1. Privacy-preserving deep learning via additively homomorphic encryption;Aono Yoshinori;IEEE Transactions on Information Forensics and Security,2017
2. Eugene Bagdasaryan, Andreas Veit, Yiqing Hua, Deborah Estrin, and Vitaly Shmatikov. 2020. How to backdoor federated learning. In International conference on artificial intelligence and statistics. PMLR, 2938--2948.
3. Aurélien Bellet, Rachid Guerraoui, Mahsa Taziki, and Marc Tommasi. 2018. Personalized and private peer-to-peer machine learning. In International Conference on Artificial Intelligence and Statistics. PMLR, 473--481.
4. Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal, and Seraphin Calo. 2019. Analyzing federated learning through an adversarial lens. In International Conference on Machine Learning. PMLR, 634--643.
5. Abhishek Bhowmick, John Duchi, Julien Freudiger, Gaurav Kapoor, and Ryan Rogers. 2018. Protection against reconstruction and its applications in private federated learning. arXiv preprint arXiv:1812.00984 (2018).