AdverTorch
AdverTorch is a Python toolbox designed for adversarial robustness research, primarily implemented in PyTorch. It provides essential functionalities for generating adversarial perturbations, defending against adversarial examples, and includes scripts for adversarial training.
Key Features:
- Adversarial Perturbation Generation: Create adversarial examples to test model robustness.
- Defense Mechanisms: Implement strategies to defend against adversarial attacks.
- Adversarial Training: Train models to be robust against adversarial examples.
- Compatibility: Developed under Python 3.6 and PyTorch 1.0.0 & 0.4.1.
- Testing Environments: Supports testing against implementations in Foolbox and CleverHans.
Benefits:
- Research Focused: Tailored for researchers in the field of adversarial machine learning.
- Open Source: Available on GitHub for contributions and collaboration.
- Active Development: Continuously updated with new features and improvements.
Highlights:
- Installation is straightforward via pip or by cloning the repository.
- Includes runnable examples for practical understanding and implementation.
- Encourages citation in research to acknowledge the use of the toolbox.
