Definition
AI security encompasses measures designed to safeguard machine learning models, data pipelines, and deployment infrastructure against threats such as adversarial attacks, data poisoning, and model inversion. It ensures the confidentiality, integrity, and availability of AI assets, maintaining trust in automated decision-making processes while complying with regulatory standards and ethical guidelines for responsible AI development.
Summary
The practice of protecting AI systems from unauthorized access, misuse, and malicious attacks.
Key Concepts
- Adversarial Robustness
- Data Privacy
- Model Integrity
- Access Control
Use Cases
- Protecting financial fraud detection models
- Securing healthcare diagnostic algorithms
- Defending autonomous vehicle perception systems