基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型
☆65May 22, 2020Updated 6 years ago
Alternatives and similar repositories for attacking_federate_learning
Users that are interested in attacking_federate_learning are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- An implementation for the paper "A Little Is Enough: Circumventing Defenses For Distributed Learning" (NeurIPS 2019)☆29Jun 29, 2023Updated 2 years ago
- ☆15May 10, 2019Updated 7 years ago
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆34Oct 11, 2024Updated last year
- PyTorch implementation of Fast-Convergent Federated Learning via Cyclic Aggregation, including FedAvg, FedProx, MOON, and FedRS☆15Jun 28, 2023Updated 2 years ago
- Byzantine-resilient distributed SGD with TensorFlow.☆40Jan 22, 2021Updated 5 years ago
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆87Feb 23, 2023Updated 3 years ago
- ☆31Apr 8, 2020Updated 6 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆150Aug 6, 2022Updated 3 years ago
- CoPur: Certifiably Robust Collaborative Inference via Feature Purification (NeurIPS 2022)☆11Dec 7, 2022Updated 3 years ago
- Accompanying source code to my Bachelor's thesis at TUHH☆11Mar 15, 2018Updated 8 years ago
- [Preprint] Backdoor Attacks on Federated Learning with Lottery Ticket Hypothesis☆10Sep 23, 2021Updated 4 years ago
- Implementation of Adversarial Privacy Graph Embedding in TensorFlow☆21Jun 12, 2020Updated 5 years ago
- DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)☆205Aug 5, 2021Updated 4 years ago
- DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation☆16Jul 13, 2020Updated 5 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Target Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning☆10Jul 2, 2019Updated 6 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆74Aug 5, 2021Updated 4 years ago
- Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data☆1,436May 7, 2024Updated 2 years ago
- A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.☆824Oct 20, 2025Updated 7 months ago
- Official implementation of "GRNN: Generative Regression Neural Network - A Data Leakage Attack for Federated Learning"☆33Feb 28, 2022Updated 4 years ago
- ☆41Feb 7, 2024Updated 2 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆153Oct 3, 2022Updated 3 years ago
- 联邦学习预测节点流量☆13Dec 5, 2020Updated 5 years ago
- The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".☆38Oct 3, 2022Updated 3 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Defending Against Backdoor Attacks Using Robust Covariance Estimation☆22Jul 12, 2021Updated 4 years ago
- ☆890Jul 27, 2024Updated last year
- Research Advances in the Latest Federal Learning Papers (Updated March 27, 2023)☆14Sep 19, 2023Updated 2 years ago
- SAFEFL: MPC-friendly Framework for Private and Robust Federated Learning☆48Aug 18, 2023Updated 2 years ago
- Learning from history for Byzantine Robustness☆26Jun 11, 2021Updated 4 years ago
- This is a simple backdoor model for federated learning.We use MNIST as the original data set for data attack and we use CIFAR-10 data set…☆14Jun 19, 2020Updated 5 years ago
- A Simulator for Privacy Preserving Federated Learning☆95Jan 12, 2021Updated 5 years ago
- ☆164Dec 23, 2022Updated 3 years ago
- An open source FL implement with dataset(Femnist, Shakespeare, MNIST, Cifar-10 and Fashion-Mnist) using pytorch☆131May 20, 2023Updated 3 years ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Github Repo for AAAI 2023 paper: On the Vulnerability of Backdoor Defenses for Federated Learning☆41Apr 3, 2023Updated 3 years ago
- ☆17Aug 5, 2024Updated last year
- Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.☆381Feb 5, 2023Updated 3 years ago
- Federated Learning Benchmark - Federated Learning on Non-IID Data Silos: An Experimental Study (ICDE 2022)☆616Feb 26, 2024Updated 2 years ago
- IEEE TIFS'20: VeriFL: Communication-Efficient and Fast Verifiable Aggregation for Federated Learning☆27Aug 22, 2022Updated 3 years ago
- Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks (ICLR '20)☆33Nov 4, 2020Updated 5 years ago
- A PyTorch Implementation of Federated Learning☆1,514Jul 25, 2024Updated last year