tianyu139 / friendly-noise
Code for Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks (NeurIPS 2022)
☆10Updated last year
Related projects: ⓘ
- Code for the paper "Autoregressive Perturbations for Data Poisoning" (NeurIPS 2022)☆18Updated last week
- Github repo for One-shot Neural Backdoor Erasing via Adversarial Weight Masking (NeurIPS 2022)☆14Updated last year
- [ICLR'21] Dataset Inference for Ownership Resolution in Machine Learning☆30Updated last year
- Not All Poisons are Created Equal: Robust Training against Data Poisoning (ICML 2022)☆17Updated 2 years ago
- ☆16Updated 10 months ago
- The official implementation of USENIX Security'23 paper "Meta-Sift" -- Ten minutes or less to find a 1000-size or larger clean subset on …☆16Updated last year
- Towards Stable Backdoor Purification through Feature Shift Tuning (NeurIPS 2023)☆22Updated last month
- The official implementation of our CVPR 2023 paper "Detecting Backdoors During the Inference Stage Based on Corruption Robustness Consist…☆19Updated last year
- [ICLR2023] Distilling Cognitive Backdoor Patterns within an Image☆30Updated 2 months ago
- ☆12Updated 2 years ago
- Image Shortcut Squeezing: Countering Perturbative Availability Poisons with Compression☆11Updated 2 months ago
- Reconstructive Neuron Pruning for Backdoor Defense (ICML 2023)☆25Updated 8 months ago
- PyTorch implementation of BPDA+EOT attack to evaluate adversarial defense with an EBM☆23Updated 4 years ago
- ICCV 2021, We find most existing triggers of backdoor attacks in deep learning contain severe artifacts in the frequency domain. This Rep…☆38Updated 2 years ago
- SEAT☆19Updated 11 months ago
- ☆27Updated 2 years ago
- [ICML 2023] Are Diffusion Models Vulnerable to Membership Inference Attacks?☆29Updated 2 weeks ago
- ☆31Updated 9 months ago
- Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation (NeurIPS 2022)☆33Updated last year
- Official repo for An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization☆11Updated 6 months ago
- Source code for ECCV 2022 Poster: Data-free Backdoor Removal based on Channel Lipschitzness☆28Updated last year
- A Unified Approach to Interpreting and Boosting Adversarial Transferability (ICLR2021)☆28Updated 2 years ago
- Official Implementation of ICLR 2022 paper, ``Adversarial Unlearning of Backdoors via Implicit Hypergradient''☆49Updated last year
- ☆14Updated last year
- Data-Efficient Backdoor Attacks☆18Updated 2 years ago
- ☆10Updated 2 years ago
- [NeurIPS'22] Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork. Haotao Wang, Junyuan Hong,…☆13Updated 9 months ago
- Code for our ICLR 2023 paper Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples.☆18Updated last year
- ☆46Updated last year
- ☆47Updated 3 years ago