---
license: apache-2.0
pipeline_tag: text-to-image
library_name: transformers
---

# 🛡️DAA: Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models

This repository contains artifacts and code related to the paper: [**Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models**](https://huggingface.co/papers/2504.20518).

Code: https://github.com/Robin-WZQ/DAA

This study introduces a novel backdoor detection perspective from **Dynamic Attention Analysis (DAA)**, which shows that the **dynamic feature in attention maps** can serve as a much better indicator for backdoor detection in text-to-image diffusion models. By examining the dynamic evolution of cross-attention maps, backdoor samples exhibit distinct feature evolution patterns compared to benign samples, particularly at the `<EOS>` token.

## 📄 Citation

If you find this project useful in your research, please consider cite:
```bibtex
@article{wang2025dynamicattentionanalysisbackdoor,
  title={Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models},
  author={Zhongqi Wang and Jie Zhang and Shiguang Shan and Xilin Chen},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
  year={2025},
}
```