| Attack Type | Description |
| Adversarial Attacks | Subtle alterations to input data that deceive AI models. |
| Data Poisoning | Deliberate corruption of the training dataset, leading to flawed learning outcomes. |
| Model Theft | Unauthorized access and duplication of AI models. |
| Infrastructure Attacks | Targeting the physical and virtual environments supporting AI systems. |