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ISACA AAISM Exam Syllabus Topics:

SectionWeightObjectives
AI Governance and Program Management31%- Stakeholder considerations and governance frameworks
  • 1. Industry frameworks and regulatory requirements
  • 2. AI governance models and oversight
- AI security program management
  • 1. Incident response and business continuity
  • 2. Program development and maintenance
- AI asset and data lifecycle management
  • 1. Data governance
  • 2. AI asset inventory and management
- AI policies and procedures
  • 1. AI-related strategy development
  • 2. Policy implementation and compliance
AI Technologies and Controls38%- AI security architecture and design
  • 1. AI infrastructure protection
  • 2. Secure AI system architecture
- AI security monitoring and operations
  • 1. Security monitoring and logging
  • 2. Operational AI controls
- Data management and privacy controls
  • 1. Privacy and ethical AI controls
  • 2. Data integrity and protection
- Trust, safety and compliance controls
  • 1. Responsible AI practices
  • 2. Compliance and governance validation
AI Risk Management31%- Third-party and supply chain risk management
  • 1. Supply chain security controls
  • 2. Vendor risk evaluation
- AI threat and vulnerability management
  • 1. AI vulnerability assessment
  • 2. Threat modeling for AI systems
- AI risk assessment and treatment
  • 1. Risk identification and analysis
  • 2. Risk thresholds and mitigation

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q234-Q239):

NEW QUESTION # 234
Differential privacy BEST helps to mitigate vulnerabilities in machine learning (ML) models by:

Answer: A

Explanation:
Differential privacy protects sensitive information by adding controlled noise during data processing or training, ensuring that the contribution of any individual data point cannot be easily identified or inferred from the model's outputs. This reduces the risk of privacy leakage and inference attacks.


NEW QUESTION # 235
An organization concerned about the ethical and responsible use of a newly developed AI product should consider implementing:

Answer: C

Explanation:
The AAISM framework highlights that organizations adopting AI must ensure accountability structures are in place to govern ethical and responsible use. An accountability model assigns clear responsibility for decisions, outputs, and risks related to AI systems. While model cards provide transparency about a model's design and performance, they are primarily documentation tools. Vendor monitoring focuses on third-party oversight, not internal accountability. Security by design improves resilience but does not by itself address ethical use. The governance approach that most directly supports responsible and ethical AI deployment is an accountability model.


NEW QUESTION # 236
When evaluating a new AI tool for intrusion prevention, which is MOST important to ensure fit within the existing program architecture?

Answer: D

Explanation:
AAISM stresses that AI tools must align with the organization's existing control objectives and governance requirements, ensuring consistency with risk management, detection philosophy, and operational processes.


NEW QUESTION # 237
When preparing for an AI incident, which of the following should be done FIRST?

Answer: B

Explanation:
AAISM incident response guidance states the first foundational step is forming a cross-functional AI-aware incident response team, including model developers, data stewards, security leads, and compliance officers. Without the team established, recovery (C), containment (D), or communication channels (A) cannot be effectively designed or executed.


NEW QUESTION # 238
Which of the following would BEST help to prevent attackers from exploiting an AI system to infer personal data?

Answer: D

Explanation:
Restricting the number of queries per user helps reduce the likelihood of inference attacks, where attackers repeatedly query an AI system to extract or reconstruct sensitive personal information from the model's responses. Limiting query volume directly constrains the attacker's ability to gather enough information for successful inference.


NEW QUESTION # 239
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