Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Reference74 articles.
1. Konečnỳ, J., McMahan, H.B., Yu, F.X., Richtárik, P., Suresh, A.T., Bacon, D.: Federated learning: strategies for improving communication efficiency. arXiv preprint arXiv:1610.05492 (2016)
2. Lyu, L., Yu, H., Yang, Q.: Threats to federated learning: a survey. arXiv e-prints, 2003 (2020)
3. Deng, Y., Zhang, T., Lou, G., Zheng, X., Jin, J., Han, Q.-L.: Deep learning-based autonomous driving systems: a survey of attacks and defenses. IEEE Trans. Ind. Inform. 17(12), 7897–7912 (2021)
4. Chen, Y., Zhu, X., Gong, X., Yi, X., Li, S.: Data poisoning attacks in internet-of-vehicle networks: taxonomy, state-of-the-art, and future directions. IEEE Trans. Ind. Inform. 19(1), 20–28 (2022)
5. Bonawitz, K., Ivanov, V., Kreuter, B., Marcedone, A., McMahan, H.B., Patel, S., Ramage, D., Segal, A., Seth, K.: Practical secure aggregation for privacy-preserving machine learning. In: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, pp. 1175–1191 (2017)