Author:
Dai Tianxiang,Duan Li,Jiang Yufan,Li Yong,Mei Fei,Sun Yulian
Publisher
Springer Nature Switzerland
Reference55 articles.
1. Araki, T., Furukawa, J., Lindell, Y., Nof, A., Ohara, K.: High-throughput semi-honest secure three-party computation with an honest majority. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, pp. 805–817 (2016)
2. Lecture Notes in Computer Science;D Bogdanov,2008
3. Bogdanov, D., Niitsoo, M., Toft, T., Willemson, J.: High-performance secure multi-party computation for data mining applications. Int. J. Inf. Secur. 11(6), 403–418 (2012)
4. Bonawitz, K.A., et al.: Practical secure aggregation for federated learning on user-held data. CoRR abs/1611.04482 (2016)
5. Byali, M., Chaudhari, H., Patra, A., Suresh, A.: Flash: fast and robust framework for privacy-preserving machine learning. Proc. Priv. Enh. Technol. 2, 459–480 (2020)
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