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ISACA AAISM Exam Syllabus Topics:

Topic	Details
Topic 1	AI Technologies and Controls: This section of the exam measures the expertise of AI Security Architects and assesses knowledge in designing secure AI architecture and controls. It addresses privacy, ethical, and trust concerns, data management controls, monitoring mechanisms, and security control implementation tailored to AI systems.
Topic 2	AI Risk Management: This section of the exam measures the skills of AI Risk Managers and covers assessing enterprise threats, vulnerabilities, and supply chain risk associated with AI adoption, including risk treatment plans and vendor oversight.
Topic 3	AI Governance and Program Management: This section of the exam measures the abilities of AI Security Governance Professionals and focuses on advising stakeholders in implementing AI security through governance frameworks, policy creation, data lifecycle management, program development, and incident response protocols.

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q220-Q225):

NEW QUESTION # 220
Personal data used to train AI systems can BEST be protected by:

A. Ensuring the quality of personal data
B. Erasing personal data after training
C. Hashing personal data
D. Anonymizing personal data

Answer: D

Explanation:
AAISM guidance on privacy-preserving AI highlights anonymization as the most effective means of protecting personal data used in training. By irreversibly removing or masking identifiable attributes, anonymization ensures that training data cannot be linked back to individuals, thereby meeting key privacy obligations under laws such as GDPR. Erasing data after training may limit exposure but does not protect it during the training process. Ensuring data quality improves accuracy but does not mitigate privacy risk.
Hashing protects data integrity but does not guarantee anonymity, as hashes can sometimes be reversed or correlated. Therefore, anonymization is the recommended control for protecting personal data in AI training.
References:
AAISM Study Guide - AI Technologies and Controls (Privacy-Preserving Methods) ISACA AI Security Management - Data Anonymization Practices

NEW QUESTION # 221
After an organization deploys an AI-based system, a regulator warns of increased risk related to AI re-identification attacks on anonymized data sets. Which of the following should the information security manager do FIRST?

A. Implement a monitoring program including privacy audits and adversarial testing
B. Establish strong access controls for services using anonymized data
C. Assume anonymization is permanent and continue regular business operations.
D. Immediately delete anonymized datasets and suspend AI services

Answer: A

Explanation:
AAISM states that anonymization is not permanent and may be reversible through re- identification attacks. The first action should be to evaluate and measure the actual privacy risk through:
- adversarial re-identification testing
- privacy audits
- monitoring for misuse
This provides the factual basis needed before making destructive or operational decisions.

NEW QUESTION # 222
Which of the following is the MAIN objective of the operational phase of AI life cycle management?

A. Optimize the model's algorithms
B. Monitor model performance
C. Obtain end-user feedback on the model
D. Align the model to business needs

Answer: B

Explanation:
In the operational phase, AAISM emphasizes continuous monitoring of models for performance, stability, robustness, drift, data quality, security events, and policy compliance. This includes telemetry, thresholds, alerts, incident response for AI failures, and evidence collection for audits. Alignment to business needs is established earlier in planning/governance; algorithmic optimization and feedback collection are supporting activities, but the primary operational objective is live monitoring and assurance to keep risk within tolerance.
References:* AI Security Management (AAISM) Body of Knowledge: AI Life Cycle-Operate/Monitor; Ongoing Performance & Drift Monitoring; AI Incident Management* AAISM Study Guide: Operational Controls, Metrics & SLAs/SLOs; Evidence & Audit Readiness in Production

NEW QUESTION # 223
As organizations increasingly rely on vendors to develop AI systems, which of the following is the MOST effective way to monitor vendors and ensure compliance with ethical and security standards?

A. Conducting regular audits of vendor processes and adherence to AI development guidelines
B. Mandating that vendors share source code and AI documentation with the contracting party
C. Allowing vendors to self-attest ethical AI compliance and implement benchmark monitoring
D. Requiring vendors to monitor their adherence to ethics and security standards

Answer: A

Explanation:
AAISM vendor governance guidance identifies regular audits of vendor processes as the most effective method of ensuring compliance with ethical and security standards. Independent audits provide verifiable assurance that vendors are meeting agreed-upon requirements. Self- attestation, internal monitoring, or documentation sharing provide some transparency but do not guarantee compliance. The best practice, particularly for high-risk AI deployments, is independent and recurring audits of vendor processes.

NEW QUESTION # 224
When selecting an AI model for a life insurance organization to enhance fraud detection, which factor is MOST critical to ensure secure and reliable deployment?

A. Robustness
B. Explainability
C. Accuracy
D. Adaptability

Answer: A

Explanation:
AAISM emphasizes robustness as the key requirement for fraud-detection systems because they must resist adversarial manipulation, data poisoning, spoofing, and input tampering.

NEW QUESTION # 225
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