BUAA-BDA / PrivacyComputing-PaperListLinks
This is a recommended paper list for the course of Privacy Computing.
☆10Updated last year
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- OLIVE: Oblivious and Differentially Private Federated Learning on TEE☆17Updated 2 years ago
- Utility-aware synthesis of differentially private and attack-resilient location traces☆25Updated 7 years ago
- ☆46Updated 2 years ago
- reveal the vulnerabilities of SplitNN☆31Updated 3 years ago
- Code for the paper "Bayesian Differential Privacy for Machine Learning"☆23Updated 5 years ago
- ☆35Updated 4 years ago
- ☆24Updated last year
- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆86Updated 2 years ago
- [arXiv'21] Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning☆22Updated 9 months ago
- Sample LDP implementation in Python☆128Updated 2 years ago
- [INFOCOM24' & TDSC25']FedPHE & Efficient and Straggler-Resistant Homomorphic Encryption for Heterogeneous Federated Learning☆41Updated 5 months ago
- The Algorithmic Foundations of Differential Pivacy by Cynthia Dwork Chinese Translation☆170Updated 3 years ago
- A curated list of advancements in Vertical Federated Learning, frameworks and libraries.☆38Updated 6 months ago
- Privacy-preserving Federated Learning with Trusted Execution Environments☆74Updated 6 months ago
- Nopeek experiments☆14Updated 5 years ago
- ☆90Updated 5 years ago
- Differential private machine learning☆200Updated 3 years ago
- A foundational platform that primarily shares federated learning, differential privacy content☆26Updated 10 months ago
- Implementing the algorithm from our paper: "A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in …☆39Updated last year
- A sybil-resilient distributed learning protocol.☆110Updated 4 months ago
- Integration of SplitNN for vertically partitioned data with OpenMined's PySyft☆28Updated 5 years ago
- Implementations of differentially private release mechanisms for graph statistics☆24Updated 3 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆67Updated 5 years ago
- Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"☆53Updated 2 years ago
- Implementation of calibration bounds for differential privacy in the shuffle model☆21Updated 5 years ago
- ☆14Updated 11 months ago
- personal implementation of secure aggregation protocol☆45Updated 2 years ago
- Federated Learning and Membership Inference Attacks experiments on CIFAR10☆23Updated 6 years ago
- Preserve data privacy with k-anonymity (samarati & mondrian), differential privacy, federated learning, paillier homomorphic encryption, …☆61Updated 4 years ago
- Implementation of the paper "Self-Balancing Federated Learning With Global Imbalanced Data in Mobile Systems"☆46Updated 2 years ago