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### Secrecy [link](https://arxiv.org/pdf/2102.01048.pdf)
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> Liagouris, John, Vasiliki Kalavri, Muhammad Faisal, and Mayank Varia. "Secrecy: Secure collaborative analytics on secret-shared data." arXiv preprint arXiv:2102.01048 (2021).
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This paper provides a solution to secure multi-party data analytics. The highlight is that this solution is based on the already secret-shared data rather than the plaintext data held by different party. The means that some optimizations base on preprocessing on plaintext input data, such as these proposed by [Conclave](https://arxiv.org/pdf/1902.06288.pdf), can not be used.
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This paper provides a solution to secure multi-party data analytics. The highlight is that this solution is based on the already secret-shared data rather than the plaintext data held by different party. This means that some optimizations base on preprocessing on plaintext input data, such as these proposed by [Conclave](https://arxiv.org/pdf/1902.06288.pdf), can not be used.
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