Megum1/ODSCAN
[IEEE S&P'24] ODSCAN: Backdoor Scanning for Object Detection Models
This project helps security researchers and machine learning engineers identify hidden malicious behaviors, known as backdoors, in object detection models. It takes a trained object detection model as input and analyzes it to determine if it has been tampered with to misclassify objects or make new, non-existent objects 'appear' when a specific trigger is present. The output indicates whether a backdoor is detected, along with visual evidence of the inverted triggers.
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Use this if you need to audit an object detection model for potential backdoor attacks, such as those that could cause misclassifications or introduce fake objects under specific conditions.
Not ideal if you are looking to defend against other types of model vulnerabilities beyond object misclassification or object appearing backdoors in detection models.
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Language
Python
License
MIT
Category
Last pushed
Oct 05, 2025
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