ix-adversarial

What problem does it solve?

This Skill enhances the robustness of machine learning models by enabling the testing of adversarial attacks and implementing defensive strategies.

Core Features & Use Cases

• Adversarial Attack Testing: Evaluate model robustness against various attack techniques like FGSM, PGD, C&W, JSMA, and UAP.
• Defensive Strategies: Implement defenses such as adversarial training, feature squeezing, statistical detection, and gradient regularization.
• Poisoning Detection: Detect poisoned data using KNN label consistency, spectral signatures, and influence functions.
• Privacy Enhancements: Apply differential privacy noise, confidence masking, and prediction purification for enhanced privacy.
• Programmatic Usage: Utilize the Skill programmatically for custom applications in adversarial machine learning research and development.

Quick Start

Run the ix-adversarial skill to test the robustness of your model against adversarial examples.