AAISM AI Technologies And Controls Practice Question
To mitigate adversarial evasion attacks against a vision model, you decide to implement defensive distillation on your TensorFlow model. What is the primary operational trade-off you must evaluate?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Reduced model sensitivity to noise and potential drop in clean accuracy
Defensive distillation increases the model's robustness against small adversarial perturbations but can lead to reduced accuracy on clean data or increased training complexity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Requirement for GPU-based training clusters only
Why it's wrong here
Distillation is not restricted to GPU-only hardware.
- ✗
Incompatibility with gradient-based optimizers
Why it's wrong here
Distillation is compatible with standard training optimizers.
- ✓
Reduced model sensitivity to noise and potential drop in clean accuracy
Why this is correct
Distillation smooths the gradient surface, which makes it harder for attackers but can impact general prediction accuracy.
- ✗
Increased latency in inference requests
Why it's wrong here
While true for some methods, it is not the primary trade-off of distillation.
About these practice questions
One of 205 original AAISM practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official ISACA exam blueprint
This AAISM practice question is part of Courseiva's free ISACA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AAISM exam.