AdrienBenamira / membership_inference_attack
Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.
β59Updated 5 years ago
Alternatives and similar repositories for membership_inference_attack:
Users that are interested in membership_inference_attack are comparing it to the libraries listed below
- π Implementation of Shokri et al(2016) "Membership Inference Attacks against Machine Learning Models"β34Updated 2 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Modelsβ125Updated 11 months ago
- Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)β48Updated 2 years ago
- β45Updated 5 years ago
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.β58Updated 5 months ago
- Code for the paper: Label-Only Membership Inference Attacksβ64Updated 3 years ago
- β69Updated 2 years ago
- Python package to create adversarial agents for membership inference attacks againts machine learning modelsβ46Updated 6 years ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)β193Updated 7 years ago
- Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"β83Updated 3 years ago
- Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)β47Updated 2 years ago
- A library for running membership inference attacks against ML modelsβ142Updated 2 years ago
- ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341β70Updated last year
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"β55Updated last year
- This repo implements several algorithms for learning with differential privacy.β106Updated 2 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)β53Updated 5 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"β30Updated 2 years ago
- Example of the attack described in the paper "Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization"β21Updated 5 years ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Longβ¦β37Updated 3 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.β131Updated 2 years ago
- Membership Inference Attacks and Defenses in Neural Network Pruningβ28Updated 2 years ago
- [ICML 2023] Official code implementation of "Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning (httβ¦β38Updated 2 months ago
- The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".β31Updated 2 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)β71Updated 3 years ago
- β31Updated 6 months ago
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"β38Updated 6 years ago
- β54Updated 2 years ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clienβ¦β76Updated 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 setβ¦β14Updated 4 years ago
- Official implementation of "GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models" (CCS 2020)β47Updated 2 years ago