Free AAISM Exam Braindumps
ISACA Advanced in AI Security Management Questions 186–190 (page: 39)

Updated On: 13-Sep-2026

Which of the following involves documenting and monitoring the complete journey of data as it flows through an AI system?

  1. Origin
  2. Lineage
  3. Processing
  4. Transformation

Answer(s): B

Explanation:

Data lineage documents and monitors the end-to-end path of data through an AI system, capturing where it came from, how it moved, and what changes occurred across the pipeline to support traceability and accountability.



A health services organization is developing a proprietary generative AI chatbot to assist patients with medical devices.
Which of the following should be the organization's HIGHEST priority?

  1. Selecting the appropriate training data
  2. Maximizing neural network size
  3. Maximizing the amount of training data
  4. Tuning algorithms used in the AI model

Answer(s): A

Explanation:

Selecting appropriate training data is the highest priority because a medical-support chatbot must be trained on accurate, relevant, and trustworthy content to reduce unsafe guidance, bias, and compliance risks; model size,
data volume, and algorithm tuning cannot compensate for poor or unsuitable data.



When using AI as part of incident response, which of the following BEST ensures the automation aligns with regulatory and governance obligations?

  1. Use deep learning models to autonomously classify all incidents.
  2. Train the AI incident response platform to mirror legacy response workflows and log containment.
  3. Apply anomaly detection models to filter incoming threats and automate containment.
  4. Implement a tiered automation strategy where severity ratings inform the need for human oversight.

Answer(s): D

Explanation:

A tiered automation strategy ties automated actions to incident severity and required approvals, ensuring high-impact decisions receive appropriate human oversight, auditability, and control consistent with governance and regulatory obligations.



Which of the following methods provides the MOST effective protection against model inversion attacks?

  1. Increasing the number of training iteration
  2. Reducing the model's complexity
  3. Implementing regularization output
  4. Using adversarial trainings

Answer(s): C

Explanation:

Regularization reduces overfitting and memorization of training data, which lowers the risk that an attacker can reconstruct sensitive training records from model outputs during a model inversion attack.



Which of the following is the MOST effective way to identify and address security risk in an AI model?

  1. Add more data to the model to increase its accuracy and reduce errors.
  2. Assign staff to review AI model outputs for accuracy.
  3. Encrypt the training data and model parameters to prevent unauthorized access.
  4. Conduct threat modeling to identify vulnerabilities and possible attack methods.

Answer(s): D

Explanation:

Threat modeling systematically identifies likely adversaries, attack surfaces, and AI-specific abuse paths (such as prompt injection, poisoning, inversion, and evasion) so controls can be selected and prioritized based on realistic security risks.



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