☆25Jan 20, 2019Updated 7 years ago
Alternatives and similar repositories for ML-Privacy-Regulization
Users that are interested in ML-Privacy-Regulization are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ☆16Apr 16, 2019Updated 7 years ago
- ☆19Mar 6, 2023Updated 3 years ago
- ☆46Nov 10, 2019Updated 6 years ago
- ☆24Dec 15, 2018Updated 7 years ago
- Code for the paper: Label-Only Membership Inference Attacks☆67Sep 11, 2021Updated 4 years ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Code for the paper "Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction" …☆13Sep 6, 2023Updated 2 years ago
- Privacy Risks of Securing Machine Learning Models against Adversarial Examples☆46Nov 25, 2019Updated 6 years ago
- ☆16Apr 4, 2024Updated 2 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆133Apr 9, 2024Updated 2 years ago
- Code for Machine Learning Models that Remember Too Much (in CCS 2017)☆31Oct 15, 2017Updated 8 years ago
- Processed datasets that we have used in our research☆15Apr 30, 2020Updated 6 years ago
- ☆13Sep 26, 2024Updated last year
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆199Nov 15, 2017Updated 8 years ago
- Shadow Attack, LiRA, Quantile Regression and RMIA implementations in PyTorch (Online version)☆14Nov 8, 2024Updated last year
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Public implementation of the paper "On the Importance of Difficulty Calibration in Membership Inference Attacks".☆16Dec 1, 2021Updated 4 years ago
- Code for Auditing Data Provenance in Text-Generation Models (in KDD 2019)☆10Jun 18, 2019Updated 6 years ago
- Code for AAAI 2021 Paper "Membership Privacy for Machine Learning Models Through Knowledge Transfer"☆11Apr 5, 2021Updated 5 years ago
- ☆12Dec 23, 2019Updated 6 years ago
- ☆12Jun 8, 2021Updated 5 years ago
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"☆37Jan 28, 2019Updated 7 years ago
- Python package to create adversarial agents for membership inference attacks againts machine learning models☆46Feb 12, 2019Updated 7 years ago
- Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)☆48Aug 18, 2022Updated 3 years ago
- ☆32Sep 2, 2024Updated last year
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.☆716Apr 26, 2025Updated last year
- Code for "Neural Network Inversion in Adversarial Setting via Background Knowledge Alignment" (CCS 2019)☆49Dec 17, 2019Updated 6 years ago
- ☆23Aug 15, 2022Updated 3 years ago
- ☆20Feb 22, 2023Updated 3 years ago
- Code for Auditing DPSGD☆39Feb 15, 2022Updated 4 years ago
- Official code for the paper "Membership Inference Attacks Against Recommender Systems" (ACM CCS 2021)☆22Oct 8, 2024Updated last year
- An awesome list of papers on privacy attacks against machine learning☆639Mar 18, 2024Updated 2 years ago
- TIPRDC: Task-Independent Privacy-Respecting Data Crowdsourcing Framework for Deep Learning with Anonymized Intermediate Representations☆20Dec 27, 2020Updated 5 years ago
- Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)☆316Jul 25, 2024Updated last year
- Proton VPN Special Offer - Get 70% off • AdSpecial partner offer. Trusted by over 100 million users worldwide. Tested, Approved and Recommended by Experts.
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆56May 28, 2019Updated 7 years ago
- ☆22Sep 17, 2024Updated last year
- A library for running membership inference attacks against ML models☆150Dec 8, 2022Updated 3 years ago
- Differential Privacy Protection against MembershipInference Attack on Machine Learning for Genomic Data☆19Aug 4, 2020Updated 5 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆136Dec 8, 2022Updated 3 years ago
- ☆18Apr 2, 2021Updated 5 years ago
- ☆20Oct 28, 2025Updated 7 months ago