An adversarial example library for constructing attacks, building defenses, and benchmarking both
Role in this project:
ML Engineer Contributions:1 review, 15 commits, 10 PRs in 8 months
Contributions summary:Adelin made several updates to the `fast_gradient_method.py` and `projected_gradient_descent.py` files, suggesting a focus on adversarial attack algorithms. These updates modified the loss function definitions, and added parameters like targeted, rand_init and rand_minmax. The user also updated `utils_tf.py`, likely to incorporate changes related to the TensorFlow framework. The contributions suggest involvement in enhancing and refining existing attack methods within the CleverHans framework.
benchmarkingmachine-learningsecurity
Contributions:21 pushes in 2 years 8 months