mmalekzadeh / honest-but-curious-nets
Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs (ACM CCS'21)
☆17Updated 2 years ago
Alternatives and similar repositories for honest-but-curious-nets
Users that are interested in honest-but-curious-nets are comparing it to the libraries listed below
Sorting:
- ☆44Updated 2 years ago
- Universal Robustness Evaluation Toolkit (for Evasion)☆31Updated last week
- ☆46Updated 4 years ago
- Code for the paper titled "Adversarial Vulnerability of Randomized Ensembles" (ICML 2022).☆10Updated 2 years ago
- ☆66Updated 4 years ago
- ☆25Updated 2 years ago
- Implementation of our ICLR 2021 paper: Policy-Driven Attack: Learning to Query for Hard-label Black-box Adversarial Examples.☆12Updated 4 years ago
- Example of the attack described in the paper "Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization"☆21Updated 5 years ago
- ☆10Updated last year
- ☆9Updated 3 years ago
- Defending Against Backdoor Attacks Using Robust Covariance Estimation☆21Updated 3 years ago
- Athena: A Framework for Defending Machine Learning Systems Against Adversarial Attacks☆42Updated 3 years ago
- ☆24Updated 2 years ago
- ☆25Updated 2 years ago
- ☆13Updated 2 years ago
- ☆24Updated 2 years ago
- ☆23Updated 2 years ago
- ☆31Updated 8 months ago
- Repo for the paper "Bounding Training Data Reconstruction in Private (Deep) Learning".☆11Updated last year
- [NeurIPS 2021] Source code for the paper "Qu-ANTI-zation: Exploiting Neural Network Quantization for Achieving Adversarial Outcomes"☆15Updated 3 years ago
- ☆12Updated 5 years ago
- Watermarking against model extraction attacks in MLaaS. ACM MM 2021.☆33Updated 3 years ago
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆34Updated 3 years ago
- Code for ML Doctor☆87Updated 9 months ago
- Defending against Model Stealing via Verifying Embedded External Features☆36Updated 3 years ago
- Privacy Risks of Securing Machine Learning Models against Adversarial Examples☆44Updated 5 years ago
- [CVPRW'22] A privacy attack that exploits Adversarial Training models to compromise the privacy of Federated Learning systems.☆12Updated 2 years ago
- Code for paper "Poisoned classifiers are not only backdoored, they are fundamentally broken"☆26Updated 3 years ago
- Membership Inference Attacks and Defenses in Neural Network Pruning☆28Updated 2 years ago
- [NeurIPS 2022] "Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets" by Ruisi Cai*, Zhenyu Zh…☆20Updated 2 years ago