- Implement adversarial training to make the model more robust against adversarial examples.
- Use input preprocessing or data augmentation techniques to reduce the effectiveness of adversarial perturbations.
- Monitor model inputs for anomalies that may indicate adversarial examples.
- Add additional layers of validation or human review for critical decisions based on AI predictions.