Koukyosyumei / Attack_SplitNN
reveal the vulnerabilities of SplitNN
☆30Updated 2 years ago
Alternatives and similar repositories for Attack_SplitNN:
Users that are interested in Attack_SplitNN are comparing it to the libraries listed below
- ☆54Updated last year
- ☆38Updated 3 years ago
- ☆34Updated 3 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆55Updated last year
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆33Updated 3 months ago
- Learning from history for Byzantine Robustness☆22Updated 3 years ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆39Updated 3 years ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆74Updated last year
- Privacy attacks on Split Learning☆37Updated 3 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆139Updated 2 years ago
- This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.☆43Updated last year
- Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent (ICLR 2021)☆20Updated 3 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆72Updated 3 years ago
- Differentially Private Federated Learning on Heterogeneous Data☆59Updated 2 years ago
- ☆67Updated 2 years ago
- This repository contains the official implementation for the manuscript: Make Landscape Flatter in Differentially Private Federated Lear…☆45Updated last year
- ☆54Updated 3 years ago
- An implementation for the paper "A Little Is Enough: Circumventing Defenses For Distributed Learning" (NeurIPS 2019)☆26Updated last year
- 基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型☆62Updated 4 years ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆37Updated 3 years ago
- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆82Updated last year
- ☆37Updated 11 months ago
- ☆15Updated 5 years ago
- Integration of SplitNN for vertically partitioned data with OpenMined's PySyft☆28Updated 4 years ago
- Github Repo for AAAI 2023 paper: On the Vulnerability of Backdoor Defenses for Federated Learning☆35Updated last year
- Eluding Secure Aggregation in Federated Learning via Model Inconsistency☆12Updated last year
- ☆16Updated 2 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆53Updated 5 years ago
- ☆25Updated 11 months ago