TinfoilHat0 / Defending-Against-Backdoors-with-Robust-Learning-RateView external linksLinks
The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".
☆35Oct 3, 2022Updated 3 years ago
Alternatives and similar repositories for Defending-Against-Backdoors-with-Robust-Learning-Rate
Users that are interested in Defending-Against-Backdoors-with-Robust-Learning-Rate are comparing it to the libraries listed below
Sorting:
- Github Repo for AAAI 2023 paper: On the Vulnerability of Backdoor Defenses for Federated Learning☆41Apr 3, 2023Updated 2 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆74Aug 5, 2021Updated 4 years ago
- [ICLR 2023, Best Paper Award at ECCV’22 AROW Workshop] FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning☆60Dec 11, 2024Updated last year
- ☆17Jun 10, 2024Updated last year
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆85Feb 23, 2023Updated 2 years ago
- [ICLR2024] "Backdoor Federated Learning by Poisoning Backdoor-Critical Layers"☆52Dec 11, 2024Updated last year
- Code Repository for the Paper ---Revisiting the Assumption of Latent Separability for Backdoor Defenses (ICLR 2023)☆47Feb 28, 2023Updated 2 years ago
- ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341☆83Apr 1, 2023Updated 2 years ago
- This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.☆46Jun 12, 2023Updated 2 years ago
- ☆54Jun 30, 2023Updated 2 years ago
- Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)☆313Jul 25, 2024Updated last year
- ☆14Oct 7, 2022Updated 3 years ago
- Eluding Secure Aggregation in Federated Learning via Model Inconsistency☆13Mar 10, 2023Updated 2 years ago
- [CVPR 2024] "Data Poisoning based Backdoor Attacks to Contrastive Learning": official code implementation.☆16Feb 10, 2025Updated last year
- Code repository for the paper --- [USENIX Security 2023] Towards A Proactive ML Approach for Detecting Backdoor Poison Samples☆30Jul 11, 2023Updated 2 years ago
- ☆31Oct 10, 2023Updated 2 years ago
- ☆73Jun 7, 2022Updated 3 years ago
- Model Poisoning Attack to Federated Recommendation☆32Apr 23, 2022Updated 3 years ago
- The core code for our paper "Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning".☆21Dec 25, 2023Updated 2 years ago
- ☆12May 6, 2022Updated 3 years ago
- Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.☆378Feb 5, 2023Updated 3 years ago
- [NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training☆32Jan 9, 2022Updated 4 years ago
- ☆27Feb 1, 2023Updated 3 years ago
- [NeurIPS 2022] "Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets" by Ruisi Cai*, Zhenyu Zh…☆21Oct 1, 2022Updated 3 years ago
- Code for "Label-Consistent Backdoor Attacks"☆57Nov 22, 2020Updated 5 years ago
- DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)☆202Aug 5, 2021Updated 4 years ago
- ☆37Apr 9, 2021Updated 4 years ago
- Official Inplementation of CVPR23 paper "Backdoor Defense via Deconfounded Representation Learning"☆25Mar 13, 2023Updated 2 years ago
- Implementation of paper "More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks"☆23May 3, 2023Updated 2 years ago
- ☆14Feb 26, 2025Updated 11 months ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆44Oct 29, 2021Updated 4 years ago
- ☆10Oct 31, 2022Updated 3 years ago
- Hybrid Federate Learning Framework for Financial Crime Detection☆13Mar 22, 2024Updated last year
- The implementation of our IEEE S&P 2024 paper "Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples".☆11Jun 28, 2024Updated last year
- Backdoor detection in Federated learning with similarity measurement☆26Apr 30, 2022Updated 3 years ago
- Multi-metrics adaptively identifies backdoors in Federated learning☆37Aug 7, 2025Updated 6 months ago
- [Preprint] Backdoor Attacks on Federated Learning with Lottery Ticket Hypothesis☆10Sep 23, 2021Updated 4 years ago
- [ECCV'24] UNIT: Backdoor Mitigation via Automated Neural Distribution Tightening☆10Dec 18, 2025Updated last month
- ☆10Jul 28, 2022Updated 3 years ago