AI Model Security

The "AI Model Security" section features AI tools and methods designed to protect machine learning models from various types of attacks and vulnerabilities. Here you will find solutions for detecting and mitigating adversarial attacks (attacks that modify input data to fool the model), protecting against model extraction or training data leakage, detecting data injection into the training process, monitoring model integrity, and ensuring data privacy. These tools are critically important for deploying robust and secure AI systems, especially in high-stakes applications (e.g., autonomous driving, healthcare, finance). They help ensure that AI models perform predictably and safely even under malicious influences.