SPIN-UMass / ML-Privacy-RegulizationLinks
☆26Updated 6 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
Sorting:
- Privacy Risks of Securing Machine Learning Models against Adversarial Examples☆44Updated 5 years ago
- ☆45Updated 5 years ago
- ☆19Updated 2 years ago
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"☆37Updated 6 years ago
- Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)☆50Updated 2 years ago
- The code is for our NeurIPS 2019 paper: https://arxiv.org/abs/1910.04749☆34Updated 5 years ago
- Craft poisoned data using MetaPoison☆52Updated 4 years ago
- ☆32Updated 10 months ago
- ☆25Updated 6 years ago
- Example of the attack described in the paper "Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization"☆21Updated 5 years ago
- Code for the paper: Label-Only Membership Inference Attacks☆65Updated 3 years ago
- ☆24Updated 2 years ago
- ☆48Updated 4 years ago
- Code for "On the Trade-off between Adversarial and Backdoor Robustness" (NIPS 2020)☆17Updated 4 years ago
- Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.☆60Updated 6 years ago
- ConvexPolytopePosioning☆35Updated 5 years ago
- Membership Inference Attacks and Defenses in Neural Network Pruning☆28Updated 3 years ago
- Official implementation of "GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models" (CCS 2020)☆48Updated 3 years ago
- RAB: Provable Robustness Against Backdoor Attacks☆39Updated last year
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆127Updated last year
- Implementation of the Model Inversion Attack introduced with Model Inversion Attacks that Exploit Confidence Information and Basic Counte…☆84Updated 2 years ago
- This is an implementation demo of the ICLR 2021 paper [Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks…☆122Updated 3 years ago
- Code for CVPR2020 paper QEBA: Query-Efficient Boundary-Based Blackbox Attack☆32Updated 4 years ago
- [ICLR'21] Dataset Inference for Ownership Resolution in Machine Learning☆32Updated 2 years ago
- ☆19Updated 4 years ago
- CVPR 2021 Official repository for the Data-Free Model Extraction paper. https://arxiv.org/abs/2011.14779☆71Updated last year
- ☆23Updated 2 years ago
- Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks (RAID 2018)☆47Updated 6 years ago
- ☆21Updated 4 years ago
- Pytorch implementation of backdoor unlearning.☆20Updated 3 years ago