Quiz ISACA - AAISM - ISACA Advanced in AI Security Management (AAISM) Exam Latest Latest Study Questions

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ISACA AAISM Exam Overview:

Certification Vendor:ISACA
Exam Name:ISACA Advanced in AI Security Management (AAISM) Exam
Exam Number:AAISM
Certificate Validity Period:3 years
Exam Price:US$459 (members), US$599 (non-members)
Exam Duration:150 minutes
Real Exam Qty:90
Related Certifications:CISM
CISSP
Passing Score:450 (out of 800)
Exam Format:Multiple-choice, Scenario-based
Available Languages:English
Recommended Training:ISACA Official AAISM Training
Exam Registration:ISACA AAISM Registration
Sample Questions:ISACA AAISM Sample Questions
Exam Way:Computer-based; available at authorized PSI testing centers or via remote proctoring
Pre Condition:Hold an active CISM or CISSP certification
Official Syllabus URL:https://www.isaca.org/credentialing/aaism/aaism-exam-content-outline

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ISACA AAISM Exam Syllabus Topics:

TopicDetails
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 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.
Topic 3
  • 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.

ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q291-Q296):

NEW QUESTION # 291
From a risk perspective, which of the following is the MOST important step when implementing an adoption strategy for AI systems?

Answer: C

Explanation:
AAISM guidance states that when adopting AI, the most important step is to conduct a risk assessment and update the enterprise risk register. This ensures AI-specific risks are identified, documented, and integrated into the organization's existing governance structures. Benchmarking peers provides context but does not address internal risk. Implementing methodologies and frameworks are important, but they precede or follow the assessment process. The decisive step that connects adoption to enterprise risk governance is updating the risk register with AI-specific risks.
References:
AAISM Study Guide - AI Risk Management (Integration with Enterprise Risk Management) ISACA AI Security Management - Risk Assessment and Register Updates


NEW QUESTION # 292
Which of the following should be done FIRST when developing an acceptable use policy for generative AI?

Answer: C

Explanation:
According to the AAISM framework, the first step in drafting an acceptable use policy is defining the scope and intended use of the AI system. This ensures that governance, regulatory considerations, risk assessments, and alignment with organizational policies are all tailored to the specific applications and functions the AI will serve. Once scope and intended use are clearly defined, legal, regulatory, and risk considerations can be systematically applied. Without this step, policies risk being generic and misaligned with business objectives.


NEW QUESTION # 293
When using data augmentation to balance an underrepresented class in a training dataset, which of the following is the GREATEST long-term risk to the AI model's real-world performance?

Answer: B

Explanation:
Data augmentation can introduce synthetic patterns that the model may learn too specifically, leading to overfitting. This reduces the model's ability to generalize to real-world data, increasing the likelihood of unexpected failures in production.


NEW QUESTION # 294
During which phase of the AI life cycle are models assessed for security and determined to be free of malicious manipulations?

Answer: D

Explanation:
The verification phase focuses on ensuring the model has been built correctly and is free from tampering or malicious manipulation by checking integrity, security controls, and adherence to design specifications before deployment.


NEW QUESTION # 295
Which of the following technologies can be used to manage deepfake risk?

Answer: B

Explanation:
The AAISM study material highlights blockchain as a control mechanism for managing deepfake risk because it provides immutable verification of digital media provenance. By anchoring original data signatures on a blockchain, organizations can verify authenticity and detect tampered or synthetic content. Data tagging helps organize but does not guarantee authenticity. MFA and adaptive authentication strengthen identity security but do not address content manipulation risks. Blockchain's immutability and traceability make it the recognized technology for mitigating deepfake challenges.
References:
AAISM Study Guide - AI Technologies and Controls (Emerging Controls for Content Authenticity) ISACA AI Governance Guidance - Blockchain for Data Integrity and Deepfake Mitigation


NEW QUESTION # 296
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