HROlive / Secure-and-Private-AI
This course introduced me to three cutting-edge technologies for privacy-preserving AI: Federated Learning, Differential Privacy, and Encrypted Computation.
☆11Updated 5 years ago
Related projects: ⓘ
- code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"☆31Updated 2 years ago
- Learning rate adaptation for differentially private stochastic gradient descent☆16Updated 3 years ago
- Simplified implementation of federated learning in PyTorch☆27Updated 3 years ago
- Unofficial pytorch implementation of paper: Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures☆24Updated 11 months ago
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆34Updated 3 years ago
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"☆38Updated 5 years ago
- Python package to create adversarial agents for membership inference attacks againts machine learning models☆46Updated 5 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆31Updated 3 years ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆37Updated 2 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆52Updated last year
- ☆21Updated 2 years ago
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆41Updated 2 years ago
- ☆25Updated 5 years ago
- Official implementation of "GRNN: Generative Regression Neural Network - A Data Leakage Attack for Federated Learning"☆27Updated 2 years ago
- Privacy Risks of Securing Machine Learning Models against Adversarial Examples☆44Updated 4 years ago
- privacy preserving deep learning☆15Updated 7 years ago
- Differentially Private Federated Learning: A Client Level Perspective☆11Updated 5 years ago
- Related material on Federated Learning☆27Updated 4 years ago
- Official code repository for our accepted work "Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning" in NeurI…☆21Updated 11 months ago
- Gradient-Leakage Resilient Federated Learning☆13Updated 2 years ago
- ☆31Updated 2 weeks ago
- DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation☆16Updated 4 years ago
- Example of the attack described in the paper "Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization"☆22Updated 4 years ago
- Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.☆47Updated 5 years ago
- [NeurIPS 2021] Source code for the paper "Qu-ANTI-zation: Exploiting Neural Network Quantization for Achieving Adversarial Outcomes"☆12Updated 2 years ago
- A PyTorch based repository for Federate Learning with Differential Privacy☆13Updated last year
- Membership Inference Attacks and Defenses in Neural Network Pruning☆25Updated 2 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆66Updated 3 years ago
- Code for Horizontal Federated Learning blog around Credit Scoring☆9Updated 4 years ago
- Adversarial attacks and defenses against federated learning.☆14Updated last year