Information-Theoretically Secure Neural Network Training with Flexible Deployment
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-44192-9_26
Reference20 articles.
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3. Catrina, O., Hoogh, S.: Improved primitives for secure multi-party integer computation. In: International Conference on Security and Cryptography for Networks, pp. 182–199 (2010)
4. Catrina, O., Saxena, A.: Secure computation with fixed-point numbers. In: International Conference on Financial Cryptography and Data Security, pp. 35–50 (2010)
5. Chaudhari, H., Rachuri, R., Suresh, A.: Trident: efficient 4pc framework for privacy preserving machine learning. In: Symposium on Network and Distributed System Security (NDSS) (2020)
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