Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)
☆56May 28, 2019Updated 6 years ago
Alternatives and similar repositories for property-inference-collaborative-ml
Users that are interested in property-inference-collaborative-ml are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Code for Machine Learning Models that Remember Too Much (in CCS 2017)☆31Oct 15, 2017Updated 8 years ago
- ☆36Jan 5, 2022Updated 4 years ago
- Code for the paper: Label-Only Membership Inference Attacks☆68Sep 11, 2021Updated 4 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Dec 8, 2022Updated 3 years ago
- Algorithms to recover input data from their gradient signal through a neural network☆317Apr 14, 2023Updated 2 years ago
- Privacy Risks of Securing Machine Learning Models against Adversarial Examples☆46Nov 25, 2019Updated 6 years ago
- Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs (ACM CCS'21)☆17Jan 11, 2023Updated 3 years ago
- Modular framework for property inference attacks on deep neural networks☆18Jun 8, 2023Updated 2 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆153Oct 3, 2022Updated 3 years ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆199Nov 15, 2017Updated 8 years ago
- The code for "Improved Deep Leakage from Gradients" (iDLG).☆166Mar 4, 2021Updated 5 years ago
- ☆19Mar 6, 2023Updated 3 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆57May 4, 2023Updated 2 years ago
- Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)☆314Jul 25, 2024Updated last year
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"☆37Jan 28, 2019Updated 7 years ago
- ☆45Nov 10, 2019Updated 6 years ago
- A pytorch implementation of the paper "Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage".☆62Oct 24, 2022Updated 3 years ago
- [NeurIPS 2019] Deep Leakage From Gradients☆476Apr 17, 2022Updated 3 years ago
- privacy preserving deep learning☆15Sep 11, 2017Updated 8 years ago
- ☆15Aug 29, 2023Updated 2 years ago
- Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"☆85Nov 22, 2021Updated 4 years ago
- Privacy-preserving federated learning is distributed machine learning where multiple collaborators train a model through protected gradi…☆31Jun 9, 2021Updated 4 years ago
- verifying machine unlearning by backdooring☆20Mar 25, 2023Updated 3 years ago
- This course introduced me to three cutting-edge technologies for privacy-preserving AI: Federated Learning, Differential Privacy, and Enc…☆11Sep 2, 2019Updated 6 years ago
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆46Nov 29, 2021Updated 4 years ago
- R-GAP: Recursive Gradient Attack on Privacy [Accepted at ICLR 2021]☆37Feb 20, 2023Updated 3 years ago
- ☆25Jan 20, 2019Updated 7 years ago
- Code for Auditing Data Provenance in Text-Generation Models (in KDD 2019)☆10Jun 18, 2019Updated 6 years ago
- code release for "Unrolling SGD: Understanding Factors Influencing Machine Unlearning" published at EuroS&P'22☆25Mar 13, 2022Updated 4 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Apr 16, 2021Updated 4 years ago
- Official code for the paper "Membership Inference Attacks Against Recommender Systems" (ACM CCS 2021)☆21Oct 8, 2024Updated last year
- The reproduction of the paper Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning.☆63Feb 2, 2023Updated 3 years ago
- Companion repository for blog post on benchmarking implementations of Paillier encryption☆19Feb 2, 2017Updated 9 years ago
- Code for the paper "Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction" …☆12Sep 6, 2023Updated 2 years ago
- Membership Inference of Generative Models☆15Oct 2, 2019Updated 6 years ago
- Raven is a Web application penetration testing tool.☆17Jun 16, 2021Updated 4 years ago
- Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets☆41Feb 25, 2023Updated 3 years ago
- Code related to the paper "Machine Unlearning of Features and Labels"☆71Feb 13, 2024Updated 2 years ago
- An awesome list of papers on privacy attacks against machine learning☆633Mar 18, 2024Updated 2 years ago