YiZeng623/frequency-backdoor
ICCV 2021, We find most existing triggers of backdoor attacks in deep learning contain severe artifacts in the frequency domain. This Repo. explores how we can use these artifacts to develop stronger backdoor defenses and attacks.
This project helps deep learning security researchers and practitioners identify and understand 'backdoor' vulnerabilities in image recognition models. It takes trained models or image datasets and reveals hidden patterns, called 'triggers,' that attackers might use. The output helps in developing ways to detect these attacks or create more stealthy ones.
No commits in the last 6 months.
Use this if you are a deep learning security researcher or practitioner working to protect or test image recognition models against hidden, malicious triggers.
Not ideal if you are looking for a general-purpose image analysis tool unrelated to deep learning security or backdoor attacks.
Stars
48
Forks
6
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Apr 27, 2022
Commits (30d)
0
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