BUAA-BDA / PrivacyComputing-PaperListLinks
This is a recommended paper list for the course of Privacy Computing.
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- Utility-aware synthesis of differentially private and attack-resilient location traces☆25Updated 6 years ago
- [arXiv'21] Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning☆22Updated 4 months ago
- [INFOCOM24' & TDSC25']FedPHE & Efficient and Straggler-Resistant Homomorphic Encryption for Heterogeneous Federated Learning☆36Updated 3 weeks ago
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- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆84Updated 2 years ago
- reveal the vulnerabilities of SplitNN☆31Updated 3 years ago
- Preserve data privacy with k-anonymity (samarati & mondrian), differential privacy, federated learning, paillier homomorphic encryption, …☆61Updated 3 years ago
- A sybil-resilient distributed learning protocol.☆105Updated 2 weeks ago
- Sample LDP implementation in Python☆129Updated 2 years ago
- The Algorithmic Foundations of Differential Pivacy by Cynthia Dwork Chinese Translation☆165Updated 2 years ago
- Useful tools for differential privacy☆218Updated 3 years ago
- ☆88Updated 5 years ago
- FedAvg code with privacy protection function, the application of Paillier homomorphic encryption algorithm and differential privacy, diff…☆126Updated 11 months ago
- OLIVE: Oblivious and Differentially Private Federated Learning on TEE☆16Updated 2 years ago
- Local Differential Privacy for Federated Learning☆17Updated 2 years ago
- Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"☆46Updated last year
- Implementing the algorithm from our paper: "A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in …☆35Updated last year
- Differential private machine learning☆195Updated 3 years ago
- Nopeek experiments☆14Updated 5 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆68Updated 4 years ago
- ☆43Updated 2 years ago
- Code for the paper "Bayesian Differential Privacy for Machine Learning"☆22Updated 5 years ago
- Implementation of local differential privacy mechanisms in Python language.☆29Updated 3 years ago
- 基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦 学习攻击模型☆64Updated 5 years ago
- Paper Notes in MPC with Applications to PPML☆71Updated last year
- Medical data is often highly sensitive in terms of data privacy and security concerns. Federated learning, one type of machine learn- ing…☆23Updated 3 years ago
- ☆35Updated 3 years ago
- An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawit…☆89Updated 6 years ago
- SAFEFL: MPC-friendly Framework for Private and Robust Federated Learning☆42Updated 2 years ago
- Integration of SplitNN for vertically partitioned data with OpenMined's PySyft☆27Updated 5 years ago