yw3xs / PPDLLinks
privacy preserving deep learning
☆15Updated 8 years ago
Alternatives and similar repositories for PPDL
Users that are interested in PPDL are comparing it to the libraries listed below
Sorting:
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆56Updated 6 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆152Updated 3 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Updated 4 years ago
- Implementation of the Model Inversion Attack introduced with Model Inversion Attacks that Exploit Confidence Information and Basic Counte…☆85Updated 2 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 3 years ago
- Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)☆312Updated last year
- A sybil-resilient distributed learning protocol.☆110Updated 4 months ago
- Privacy-Preserving Deep Learning via Additively Homomorphic Encryption☆72Updated 5 years ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆200Updated 8 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆74Updated 4 years ago
- Salvaging Federated Learning by Local Adaptation☆56Updated last year
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Updated 4 years ago
- code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"☆31Updated 3 years ago
- ☆12Updated 6 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆57Updated 2 years ago
- ☆31Updated 5 years ago
- Related material on Federated Learning☆26Updated 5 years ago
- The code for "Improved Deep Leakage from Gradients" (iDLG).☆165Updated 4 years ago
- Privacy Risks of Securing Machine Learning Models against Adversarial Examples☆46Updated 6 years ago
- DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)☆202Updated 4 years ago
- ☆28Updated 2 years ago
- This is an implementation for paper "A Hybrid Approach to Privacy Preserving Federated Learning" (https://arxiv.org/pdf/1812.03224.pdf)☆23Updated 5 years ago
- simple Differential Privacy in PyTorch☆49Updated 5 years ago
- Privacy attacks on Split Learning☆43Updated 4 years ago
- ☆46Updated 6 years ago
- A Simulator for Privacy Preserving Federated Learning☆96Updated 5 years ago
- Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"☆85Updated 4 years ago
- ☆90Updated 5 years ago
- The reproduction of the paper Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning.☆63Updated 2 years ago
- Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent (ICLR 2021)☆21Updated 4 years ago