yonsei-sslab / MIALinks
π Implementation of Shokri et al(2016) "Membership Inference Attacks against Machine Learning Models"
β36Updated 2 years ago
Alternatives and similar repositories for MIA
Users that are interested in MIA are comparing it to the libraries listed below
Sorting:
- Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.β60Updated 6 years ago
- Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)β47Updated 3 years ago
- Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)β50Updated 2 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Modelsβ126Updated last year
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.β62Updated 8 months ago
- Code for the paper: Label-Only Membership Inference Attacksβ65Updated 3 years ago
- This repo implements several algorithms for learning with differential privacy.β107Updated 2 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"β56Updated 2 years ago
- Code related to the paper "Machine Unlearning of Features and Labels"β69Updated last year
- β55Updated 2 years ago
- [ICML 2023] Official code implementation of "Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning (httβ¦β41Updated 5 months ago
- β69Updated 2 years ago
- A pytorch implementation of the paper "Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage".β58Updated 2 years ago
- β29Updated last year
- Official codes for "Understanding Deep Gradient Leakage via Inversion Influence Functions", NeurIPS 2023β16Updated last year
- Code for ML Doctorβ88Updated 9 months ago
- Membership Inference Attacks and Defenses in Neural Network Pruningβ28Updated 2 years ago
- ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341β73Updated 2 years ago
- β73Updated 3 years ago
- β37Updated 3 years ago
- [ICLR 2023, Best Paper Award at ECCVβ22 AROW Workshop] FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learningβ56Updated 5 months ago
- β45Updated 5 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"β32Updated 3 years ago
- β37Updated 4 years ago
- [ICLR2024] "Backdoor Federated Learning by Poisoning Backdoor-Critical Layers"β37Updated 5 months ago
- Fast, memory-efficient, scalable optimization of deep learning with differential privacyβ120Updated 2 weeks ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clienβ¦β83Updated 2 years ago
- The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".β33Updated 2 years ago
- [USENIX Security 2022] Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architectureβ16Updated 2 years ago
- Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfoβ¦β41Updated last year