sisaman / LPGNN
Locally Private Graph Neural Networks (ACM CCS 2021)
☆45Updated last year
Alternatives and similar repositories for LPGNN:
Users that are interested in LPGNN are comparing it to the libraries listed below
- [IEEE S&P 22] "LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis" by Fan Wu, Yunhui Long, Ce Zhang, …☆23Updated 3 years ago
- GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)☆47Updated last year
- ☆14Updated 4 years ago
- Implementations of differentially private release mechanisms for graph statistics☆23Updated 2 years ago
- Implementation of Adversarial Privacy Graph Embedding in TensorFlow☆19Updated 4 years ago
- Code for Subgraph Federated Learning with Missing Neighbor Generation (NeurIPS 2021)☆74Updated 3 years ago
- ☆10Updated 3 years ago
- ☆16Updated 3 years ago
- ☆28Updated last year
- ☆32Updated 3 years ago
- This repository is the implementation of Federated Graph Classification over Non-IID Graphs.☆42Updated last year
- FedGraphNN: A Federated Learning Platform for Graph Neural Networks with MLOps Support. The previous research version is accepted to ICLR…☆180Updated last year
- SpreadGNN: Serverless Multi-Task Learning Framework for Graph Neural Networks. Accepted to AAAI22.☆47Updated 2 years ago
- [AAAI'23] Federated Learning on Non-IID Graphs via Structural Knowledge Sharing☆62Updated 2 years ago
- ☆15Updated 5 years ago
- This repository aims to provide links to works about privacy attacks and privacy preservation on graph data with Graph Neural Networks (G…☆22Updated last year
- ☆55Updated 2 years ago
- Implementation of "PrivGraph: Differentially Private Graph Data Publication by Exploiting Community Information"☆13Updated 2 years ago
- Code for CCS '23 paper "Blink: Link Local Differential Privacy in Graph Neural Networks via Bayesian Estimation"☆11Updated last year
- Official implementation of "Graph Unlearning" (ACM CCS 2022)☆47Updated 2 years ago
- A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)☆38Updated 3 years ago
- ☆11Updated 2 years ago
- Official Code for FedGCN [NeurIPS 2023]☆64Updated 3 months ago
- 基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型☆62Updated 4 years ago
- ☆42Updated 11 months ago
- Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness (IJCAI'19).☆13Updated 4 years ago
- Official Pytorch implementation of IJCAI'21 paper "GraphMI: Extracting Private Graph Data from Graph Neural Networks"☆13Updated 3 years ago
- Implementation of paper "More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks"☆23Updated last year
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Updated 7 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆73Updated 3 years ago