MichaelTJC96 / Label_Flipping_AttackLinks
The project aims to evaluate the vulnerability of Federated Learning systems to targeted data poisoning attack known as Label Flipping Attack. The project studies the scenario that a malicious participant can only manipulate the raw training data on their device. Hence, non-expert malicious participants can achieve poisoning without knowing the …
☆19Updated 3 years ago
Alternatives and similar repositories for Label_Flipping_Attack
Users that are interested in Label_Flipping_Attack are comparing it to the libraries listed below
Sorting:
- FedAvg code with privacy protection function, the application of Paillier homomorphic encryption algorithm and differential privacy, diff…☆126Updated last year
- Code for Data Poisoning Attacks Against Federated Learning Systems☆200Updated 4 years ago
- Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shak…☆404Updated 11 months ago
- Implementation of dp-based federated learning framework using PyTorch☆308Updated 2 years ago
- nips23-Dynamic Personalized Federated Learning with Adaptive Differential Privacy☆84Updated last year
- Paper notes and code for differentially private machine learning☆359Updated last month
- IEEE TIFS'20: VeriFL: Communication-Efficient and Fast Verifiable Aggregation for Federated Learning☆25Updated 3 years ago
- FedShare: Secure Aggregation based on Additive Secret Sharing in Federated Learning☆20Updated 2 years ago
- We provide a friendly foundational platform for beginners who intend to start Federated Learning (FL)☆17Updated 4 months ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆148Updated 3 years ago
- An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawit…☆88Updated 6 years ago
- An open source FL implement with dataset(Femnist, Shakespeare, MNIST, Cifar-10 and Fashion-Mnist) using pytorch☆131Updated 2 years ago
- Official Implementation of "Lurking in the shadows: Unveiling Stealthy Backdoor Attacks against Personalized Federated Learning"☆10Updated 8 months ago
- reproduce the FLTrust model based on the paper "FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping"☆32Updated 2 years ago
- Implementing the algorithm from our paper: "A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in …☆36Updated last year
- ☆40Updated last year
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆35Updated last year
- ⚔️ Blades: A Unified Benchmark Suite for Attacks and Defenses in Federated Learning☆148Updated 7 months ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆67Updated 4 years ago
- Preserve data privacy with k-anonymity (samarati & mondrian), differential privacy, federated learning, paillier homomorphic encryption, …☆61Updated 3 years ago
- A sybil-resilient distributed learning protocol.☆104Updated last month
- A foundational platform that primarily shares federated learning, differential privacy content☆24Updated 6 months ago
- ☆35Updated 3 years ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆84Updated 2 years ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆33Updated 4 years ago
- An implementation of Deep Learning with Differential Privacy☆26Updated 2 years ago
- Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)☆306Updated last year
- personal implementation of secure aggregation protocol☆45Updated last year
- ☆16Updated last year
- DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)☆198Updated 4 years ago