Harry24k/PGD-pytorch
A pytorch implementation of "Towards Deep Learning Models Resistant to Adversarial Attacks"
This project helps machine learning engineers and researchers evaluate how vulnerable their image classification models are to malicious inputs. It takes a pre-trained image classification model and an image, then generates a slightly modified (adversarial) image that tricks the model into misclassifying it. This is useful for understanding and improving the robustness of AI systems in security-sensitive applications.
159 stars. No commits in the last 6 months.
Use this if you need to test the resilience of your deep learning image classification models against subtle, intentionally designed attacks that could cause misclassifications.
Not ideal if you are looking for a general-purpose library of various adversarial attacks, as this project specifically implements the PGD attack and is no longer updated.
Stars
159
Forks
40
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 04, 2019
Commits (30d)
0
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