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ISACA AAISM Exam Overview:

Certification Vendor:ISACA
Exam Name:Advanced in AI Security Management (AAISM) Exam
Exam Number:AAISM
Exam Format:Multiple-choice questions
Related Certifications:CISSP
CISM
Real Exam Qty:90
Available Languages:English, Spanish
Exam Price:USD 459 (member) / USD 599 (non-member)
Certificate Validity Period:3 years (continuing professional education required for renewal)
Passing Score:450/800
Exam Duration:150 minutes
Recommended Training:ISACA Official Training & Review Materials
Exam Registration:ISACA AAISM Credentialing Page
Sample Questions:ISACA AAISM Sample Questions
Exam Way:Computer-based exam (online proctored or authorized test center)
Pre Condition:Recommended: Active CISM or CISSP certification and experience in IT/security management or advisory roles
Official Syllabus URL:https://www.isaca.org/credentialing/aaism

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ISACA AAISM 考試大綱：

主題簡介
主題 1
  • 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.
主題 2
  • 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.
主題 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.

最新的 ISACA AAISM Certification AAISM 免費考試真題 (Q127-Q132):

問題 #127
Which of the following should be the PRIMARY objective of implementing differential privacy techniques in AI models used for fraud detection systems?

答案：B

解題說明：
AAISM defines differential privacy as a technique that ensures individual data points cannot be reverse- engineered or identified, even when used to train high-risk AI models such as fraud detection systems. Its primary purpose is to protect individual privacy while maintaining aggregate utility.
Accuracy improvements (B) or performance optimizations (A, D) are not core objectives of differential privacy.
References: AAISM Study Guide - Privacy-Preserving Machine Learning; Differential Privacy Fundamentals.


問題 #128
When robust input controls are not practical on a large language model (LLM) to prevent prompt injection attacks from external threats, which of the following would be the BEST compensating control to address the risk?

答案：D

解題說明：
When preventive input hardening isn't feasible for LLMs, AAISM prescribes compensating detective and corrective controls--notably human review and annotation of outputs prior to downstream action--to reduce harm from prompt injection. Output-side review gates prevent untrusted instructions from propagating, enable rapid suppression/feedback loops, and provide labeled examples for subsequent model hardening.


問題 #129
An organization lacks visibility into the decision-making processes of a newly deployed AI model, and there are concerns regarding accuracy, bias, and stakeholder trust. Which of the following is the BEST way to improve model accuracy?

答案：A

解題說明：
Expanding the training dataset with diverse and representative scenarios improves the model's ability to generalize and reduces errors, directly enhancing accuracy.


問題 #130
An organization is facing a deepfake attack intended to manipulate stock prices. The organization's crisis communication plan has been activated. Which of the following is MOST important to include in the initial response?

答案：A

解題說明：
AAISM guidance on crisis management and communication emphasizes that the initial priority in responding to a reputational or market manipulation attack is to provide accurate clarifying information to the public through a pre-approved statement. This ensures stakeholders and markets are given verified facts immediately, limiting the spread of misinformation. While forensic analysis, employee training, and monitoring activities are important, they occur after the immediate need for public trust and damage control is addressed. Pre-approved statements are a central control in AI-related incident response to ensure consistency, timeliness, and credibility in communications.
References:
AAISM Study Guide - AI Governance and Program Management (Incident Response and Crisis Communication) ISACA AI Security Management - Public Communication and Trust Preservation


問題 #131
Secure aggregation enhances the security of federated learning systems by:

答案：C

解題說明：
Secure aggregation cryptographically aggregates client updates so that the server learns only the sum/aggregate, not any single client's update. Properly implemented, the server cannot recover individual contributions--even if compromised--thereby preserving client confidentiality.


問題 #132
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