AI-secure / DataLensLinks
[CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long*, Luka Rimanic, Ce Zhang, Bo Li
☆38Updated 3 years ago
Alternatives and similar repositories for DataLens
Users that are interested in DataLens are comparing it to the libraries listed below
Sorting:
- This repo implements several algorithms for learning with differential privacy.☆109Updated 2 years ago
- ☆54Updated 2 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆57Updated 2 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆73Updated 4 years ago
- Privacy attacks on Split Learning☆42Updated 3 years ago
- ☆70Updated 3 years ago
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.☆63Updated 10 months ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆54Updated 6 years ago
- Official code for "Personalized Federated Learning through Local Memorization" (ICML'22)☆42Updated 2 years ago
- Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)☆48Updated 3 years ago
- Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)☆50Updated 3 years ago
- Code for the paper: Label-Only Membership Inference Attacks☆66Updated 3 years ago
- The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".☆34Updated 2 years ago
- ☆15Updated 2 years ago
- ☆54Updated 4 years ago
- [NeurIPS 2022] JAX/Haiku implementation of "On Privacy and Personalization in Cross-Silo Federated Learning"☆27Updated 2 years ago
- ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341☆73Updated 2 years ago
- ☆37Updated 3 years ago
- The code for "Improved Deep Leakage from Gradients" (iDLG).☆153Updated 4 years ago
- ☆40Updated last year
- ☆45Updated 5 years ago
- A pytorch implementation of the paper "Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage".☆59Updated 2 years ago
- Learning from history for Byzantine Robustness☆24Updated 4 years ago
- ☆42Updated 2 years ago
- Code for ML Doctor☆91Updated last year
- R-GAP: Recursive Gradient Attack on Privacy [Accepted at ICLR 2021]☆37Updated 2 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆33Updated 4 years ago
- ☆39Updated 4 years ago
- ☆22Updated 3 years ago
- ☆30Updated 5 years ago