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:
- ☆38Apr 9, 2021Updated 5 years ago
- An implementation for the paper "A Little Is Enough: Circumventing Defenses For Distributed Learning" (NeurIPS 2019)☆29Jun 29, 2023Updated 3 years ago
- ☆16May 10, 2019Updated 7 years ago
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆35Oct 11, 2024Updated last year
- PyTorch implementation of Fast-Convergent Federated Learning via Cyclic Aggregation, including FedAvg, FedProx, MOON, and FedRS☆15Jun 28, 2023Updated 3 years ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- Byzantine-resilient distributed SGD with TensorFlow.☆40Jan 22, 2021Updated 5 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆153Aug 6, 2022Updated 4 years ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆87Feb 23, 2023Updated 3 years ago
- CoPur: Certifiably Robust Collaborative Inference via Feature Purification (NeurIPS 2022)☆11Dec 7, 2022Updated 3 years ago
- ☆31Apr 8, 2020Updated 6 years ago
- Accompanying source code to my Bachelor's thesis at TUHH☆11Mar 15, 2018Updated 8 years ago
- 自己的个人毕设，联邦学习相关，主要是多方安全计算中秘密分享的一种算法实现，以完成不需要第三方的安全隐私传输。（An algorithm implementation of secret sharing in multi-party secure computing to c…☆18Apr 10, 2022Updated 4 years ago
- Implementation of Adversarial Privacy Graph Embedding in TensorFlow☆21Jun 12, 2020Updated 6 years ago
- ☆54Feb 19, 2023Updated 3 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.
- DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)☆206Aug 5, 2021Updated 5 years ago
- DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation☆16Jul 13, 2020Updated 6 years ago
- ☆20Apr 12, 2023Updated 3 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆75Aug 5, 2021Updated 5 years ago
- Target Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning☆10Jul 2, 2019Updated 7 years ago
- Code for the paper "Knowledge-Aware Federated Active Learning with Non-IID Data", ICCV2023☆10Sep 8, 2023Updated 2 years ago
- Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data☆1,438May 7, 2024Updated 2 years ago
- 联邦学习预测节点流量☆13Dec 5, 2020Updated 5 years ago
- A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.☆828Oct 20, 2025Updated 9 months ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- ☆42Feb 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
- ⚔️ Blades: A Unified Benchmark Suite for Attacks and Defenses in Federated Learning☆157Feb 16, 2025Updated last year
- The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".☆38Oct 3, 2022Updated 3 years ago
- ☆894Jul 27, 2024Updated 2 years ago
- Defending Against Backdoor Attacks Using Robust Covariance Estimation☆22Jul 12, 2021Updated 5 years ago
- A Simulator for Privacy Preserving Federated Learning☆94Jan 12, 2021Updated 5 years ago
- Github Repo for AAAI 2023 paper: On the Vulnerability of Backdoor Defenses for Federated Learning☆41Apr 3, 2023Updated 3 years ago
- ☆25Nov 13, 2025Updated 9 months ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- SAFEFL: MPC-friendly Framework for Private and Robust Federated Learning☆48Aug 18, 2023Updated 2 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…☆15Jun 19, 2020Updated 6 years ago
- Research Advances in the Latest Federal Learning Papers (Updated March 27, 2023)☆14Sep 19, 2023Updated 2 years ago
- 这是本人使用python搭建的区块链demo，仅包含网络层，用于学习用途☆12May 11, 2018Updated 8 years ago
- ☆17Aug 5, 2024Updated 2 years ago
- Learning from history for Byzantine Robustness☆27Jun 11, 2021Updated 5 years ago
- An open source FL implement with dataset(Femnist, Shakespeare, MNIST, Cifar-10 and Fashion-Mnist) using pytorch☆132May 20, 2023Updated 3 years ago