shilab / DP-MIA
Differential Privacy Protection against MembershipInference Attack on Machine Learning for Genomic Data
☆16Updated 4 years ago
Alternatives and similar repositories for DP-MIA:
Users that are interested in DP-MIA are comparing it to the libraries listed below
- This repo implements several algorithms for learning with differential privacy.☆106Updated 2 years ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆37Updated 3 years ago
- Learning from history for Byzantine Robustness☆22Updated 3 years ago
- Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…☆41Updated 11 months ago
- Robust aggregation for federated learning with the RFA algorithm.☆48Updated 2 years ago
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.☆58Updated 5 months ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆30Updated 2 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆55Updated last year
- ☆20Updated 5 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆71Updated 3 years ago
- simple Differential Privacy in PyTorch☆48Updated 4 years ago
- The code for "Improved Deep Leakage from Gradients" (iDLG).☆148Updated 4 years ago
- ☆14Updated last year
- Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent (ICLR 2021)☆20Updated 3 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆142Updated 2 years ago
- ☆14Updated last year
- ☆35Updated 3 years ago
- Adversarial attacks and defenses against federated learning.☆15Updated last year
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆147Updated 2 years ago
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Updated 7 years ago
- Code for the paper: Label-Only Membership Inference Attacks☆64Updated 3 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆33Updated 3 years ago
- ☆18Updated 3 years ago
- ☆54Updated 3 years ago
- Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)☆48Updated 2 years ago
- ☆27Updated 2 years ago
- An implementation for the paper "A Little Is Enough: Circumventing Defenses For Distributed Learning" (NeurIPS 2019)☆26Updated last year
- ☆38Updated 3 years ago
- ☆54Updated 2 years ago
- ☆69Updated 2 years ago