What does Adversarial Inference aim to achieve?

• A. To make the AI model more resilient using regularization techniques and defensive distillation.
• B. To bypass security by authenticating attackers.
• C. To increase model complexity without defense.
• D. To ignore adversarial inputs.

Answer: (A)

Adversarial inference aims to make AI models more robust against adversarial inputs during inference by applying defensive techniques such as regularization and defensive distillation. Regularization helps prevent the model from relying on fragile patterns, encouraging smoother decision boundaries and better generalization to small input perturbations. Defensive distillation trains a model using softened output probabilities from a teacher model, which tends to dampen gradients and reduce sensitivity to subtle input changes that attackers exploit. These approaches focus on resilience and reliable performance in the face of adversarial perturbations, rather than enabling attacks, increasing unhelpful complexity, or ignoring adversarial inputs.