BUAA-BDA / PrivacyComputing-PaperListLinks
This is a recommended paper list for the course of Privacy Computing.
☆11Updated last year
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- OLIVE: Oblivious and Differentially Private Federated Learning on TEE☆16Updated 2 years ago
- Utility-aware synthesis of differentially private and attack-resilient location traces☆24Updated 6 years ago
- [arXiv'21] Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning☆22Updated 2 months ago
- ☆19Updated last year
- Privacy-preserving Federated Learning with Trusted Execution Environments☆68Updated 2 years ago
- ☆14Updated 4 months ago
- Implementation of calibration bounds for differential privacy in the shuffle model☆22Updated 4 years ago
- Efficient and Straggler-Resistant Homomorphic Encryption for Heterogeneous Federated Learning☆31Updated last week
- ☆41Updated last year
- Implementations of differentially private release mechanisms for graph statistics☆24Updated 3 years ago
- This is an implementation for paper "A Hybrid Approach to Privacy Preserving Federated Learning" (https://arxiv.org/pdf/1812.03224.pdf)☆21Updated 5 years ago
- Implementation of local differential privacy mechanisms in Python language.☆29Updated 2 years ago
- Code for the paper "Bayesian Differential Privacy for Machine Learning"☆22Updated 4 years ago
- ☆88Updated 5 years ago
- ☆35Updated 3 years ago
- Nopeek experiments☆14Updated 5 years ago
- Locally Private Graph Neural Networks (ACM CCS 2021)☆47Updated last year
- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆84Updated 2 years ago
- ☆35Updated 2 years ago
- Local Differential Privacy for Federated Learning☆16Updated 2 years ago
- A foundational platform that primarily shares federated learning, differential privacy content☆22Updated 3 months ago
- reveal the vulnerabilities of SplitNN☆31Updated 3 years ago
- Privacy attacks on Split Learning☆42Updated 3 years ago
- The Algorithmic Foundations of Differential Pivacy by Cynthia Dwork Chinese Translation☆164Updated 2 years ago
- Privacy-Preserving Gradient Boosting Decision Trees (AAAI 2020)☆27Updated last year
- An implementation for the paper "A Little Is Enough: Circumventing Defenses For Distributed Learning" (NeurIPS 2019)☆26Updated 2 years ago
- Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"☆46Updated last year
- [USENIX Security'24] Lotto: Secure Participant Selection against Adversarial Servers in Federated Learning☆19Updated 2 months ago
- Repository for collection of research papers on multi-party learning.☆32Updated last year
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.☆62Updated 8 months ago