Dopamine: Differentially Private Federated Learning on Medical Data (AAAI - PPAI)
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Updated
Sep 13, 2021 - Python
Dopamine: Differentially Private Federated Learning on Medical Data (AAAI - PPAI)
Secure Aggregation with Shamir’s Method
A scheme to implement finite groups as oblivious data structures. The oblivious operations are defined by a set of secure multiparty computation (MPC) protocols. Practical protocols are presented for the group of quadratic residues, elliptic curves groups and class groups of imaginary quadratic orders.
Oblivious transfer (OT) communications protocol message/response functionality implementations based on Curve25519 and the Ristretto group.
Embedded domain-specific combinator library for the abstract assembly and automated synthesis of logical circuits.
A tool for XAG Error Estimation
Delta node receives Delta tasks, distributes them across the network and executes tasks from the network.
Data structure for representing secret shares of byte vectors based on bitwise XOR, designed for use within secure multi-party computation (MPC) protocol implementations.
Data structure for representing additive secret shares of integers, designed for use within secure multi-party computation (MPC) protocol implementations.
Flower-based Privacy-Preserving Federated Learning with secure aggregation using Carbyne Stack
Python library that serves as an API for common cryptographic primitives used to implement OPRF, OT, and PSI protocols.
A scheme that produces a zero-knowledge proof of correctness for an MPC computation. The scheme allows anyone, particularly someone external to the secure computation, to check the correctness of the output, while preserving the privacy properties of the MPC protocol.
Minimal pure-Python implementation of a secure multi-party computation (MPC) protocol for evaluating arithmetic sum-of-products expressions via a non-interactive computation phase.
Fault-tolerant secure multiparty computation in Python.
MPyC: Multiparty Computation in Python
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