
The author introduces the Bicoptor protocol to enhance the efficiency of evaluating non-linear functions in privacy-preserving machine learning, focusing on sign determination and common non-linear functions. The approach involves a two-round communication process without preprocessing.


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bicoptor-efficient-secure-three-party-computation-for-privacy-preserving-machine-learning


Bicoptor: Efficient Secure Three-party Computation for Privacy-preserving Machine Learning


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The authors propose Taypsi, a language that statically enforces privacy policies in MPC applications, eliminating dynamic overhead. This approach improves performance significantly.


taypsi-static-enforcement-of-privacy-policies-for-policy-agnostic-oblivious-computation


Taypsi: Static Enforcement of Privacy Policies for Policy-Agnostic Oblivious Computation
