Collateral Learning - Functional Encryption and Adversarial Training on partially encrypted networks
-
Updated
Jul 25, 2024 - Jupyter Notebook
Collateral Learning - Functional Encryption and Adversarial Training on partially encrypted networks
A lightweight Key-Policy Attribute-Based Encryption scheme in C++
Functional encryption library for python
Python implementation of some existing functional encryption schemes for the inner product functionality
Celestia proxy service enabling Private Blockspace
Implementation of Few Interesting Functional Encryption Schemes
PyFE4AI is a research-oriented Python library for functional encryption in trustworthy AI systems.
A collection of research and survey papers of differential privacy and federated learning
Federated unlearning through functional encryption.
Functional encryption for federated learning with weight clustering and probabilistic filters.
The True Blue Goddess System of Cryptography
GPU-accelerated functional encryption with CUDA BSGS and validated MNIST benchmarks.
Crypto for Biometrics
WIP: Practical implementation of ABE (Attribute-Based Encryption) in TypeScript. Currently focusing on CP-ABE.
Covariance learning and finite-bit reconstruction for an explicit quadratic tensor functional-encryption family.
GPU-accelerated functional encryption with CUDA BSGS and validated MNIST benchmarks.
Browser-based inner-product functional encryption demo — ABDP15 (PKC 2015) over ristretto255. A key releasing only ⟨x, y⟩ beside one releasing the whole vector, the baby-step giant-step bottleneck measured in group operations, exact reconstruction from enough keys. Issue one key too many and you hand over the master secret.
To associate your repository with the functional-encryption topic, visit your repo's landing page and select "manage topics."