This repository contains artifacts and code related to the paper: Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models.

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.

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