BUAA-BDA / PrivacyComputing-PaperListLinks
This is a recommended paper list for the course of Privacy Computing.
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- OLIVE: Oblivious and Differentially Private Federated Learning on TEE☆17Updated 2 years ago
- ☆24Updated last year
- [arXiv'21] Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning☆22Updated 9 months ago
- Preserve data privacy with k-anonymity (samarati & mondrian), differential privacy, federated learning, paillier homomorphic encryption, …☆61Updated 4 years ago
- Utility-aware synthesis of differentially private and attack-resilient location traces☆25Updated 7 years ago
- Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"☆53Updated 2 years ago
- Privacy-preserving Federated Learning with Trusted Execution Environments☆74Updated 6 months ago
- ☆90Updated 5 years ago
- This is an implementation for paper "A Hybrid Approach to Privacy Preserving Federated Learning" (https://arxiv.org/pdf/1812.03224.pdf)☆24Updated 5 years ago
- Nopeek experiments☆14Updated 5 years ago
- personal implementation of secure aggregation protocol☆45Updated 2 years ago
- Sample LDP implementation in Python☆128Updated 2 years ago
- A sybil-resilient distributed learning protocol.☆110Updated 4 months ago
- reveal the vulnerabilities of SplitNN☆31Updated 3 years ago
- Code for the paper "Bayesian Differential Privacy for Machine Learning"☆23Updated 5 years ago
- An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawit…☆92Updated 6 years ago
- Integration of SplitNN for vertically partitioned data with OpenMined's PySyft☆28Updated 5 years ago
- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆86Updated 2 years ago
- Federated Learning and Membership Inference Attacks experiments on CIFAR10☆23Updated 6 years ago
- ☆46Updated 2 years ago
- Code for Paper "Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption"☆34Updated 3 years ago
- Privacy-preserving federated learning is distributed machine learning where multiple collaborators train a model through protected gradi…☆31Updated 4 years ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆85Updated 2 years ago
- Differential private machine learning☆200Updated 3 years ago
- FedAvg code with privacy protection function, the application of Paillier homomorphic encryption algorithm and differential privacy, diff…☆132Updated last year
- ☆35Updated 4 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆67Updated 5 years ago
- THU-AIR Vertical Federated Learning general, extensible and light-weight framework☆102Updated last year
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆148Updated 3 years ago
- Local Differential Privacy for Federated Learning☆19Updated 3 years ago