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認定する-100％合格率のAAISM全真模擬試験試験-試験の準備方法AAISM更新版

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ISACA AAISM 認定試験の出題範囲：

トピック
出題範囲

トピック 1

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.

トピック 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.

トピック 3

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.

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ISACA Advanced in AI Security Management (AAISM) Exam 認定 AAISM 試験問題 (Q126-Q131):

質問 # 126
An organization is deploying a large language model (LLM) and is concerned that input manipulations may compromise its integrity. Which of the following is the MOST effective way to determine an acceptable risk threshold?

A. Assess the business impact of known threats
B. Implement a static risk threshold by limiting LLM outputs
C. Restrict all user inputs containing special characters
D. Deploy a real-time logging and monitoring system

正解：A

解説：
AAISM requires that risk thresholds/tolerances be set by aligning threat likelihood and impact with the organization's business context and risk appetite. Determining "acceptable" risk starts with assessing business impact of credible threats (e.g., prompt injection leading to data exfiltration, policy evasion, or harmful actions), then translating this into control intensity and thresholds. Hard input restrictions (A) and static output caps (C) are blunt measures that may degrade utility without ensuring alignment to risk appetite.
Monitoring (B) is essential for detection, but it does not, by itself, define what level of risk is acceptable.
References: AI Security Management (AAISM) Body of Knowledge - Risk Appetite and Tolerance for AI; Threat Modeling for LLMs; Business Impact Analysis and Risk Acceptance Criteria.

質問 # 127
A global organization has experienced multiple incidents of staff copying confidential data into public chatbots and acting on the model outputs. Which of the following is MOST important to reduce short-term risk when launching an AI security awareness initiative?

A. Requiring employees to complete an annual generic phishing and deepfake awareness module
B. Delivering role-based and scenario-driven AI security training mapped to policy and job functions
C. Publishing an AI acceptable use policy and collecting e-signatures of employees
D. Blocking access to public large language models (LLMs) at the network perimeter

正解：B

解説：
AAISM prescribes targeted, role-based, scenario-driven training aligned to policy and job tasks as the highest- impact near-term intervention for human-factor AI risks. By mapping concrete "do/don't" behaviors (e.g., what data may/may not be pasted into public chatbots, required redaction steps, approved tools, verification of outputs) to specific roles, organizations rapidly reduce incident likelihood and harmful actions.
* A (blocking) is a technical containment option but is not an awareness-initiative control and may cause workarounds; AAISM treats it as complementary, not a substitute for behavior change.
* B generic modules fail to address the specific misuse pattern.
* D signatures provide attestations without ensuring comprehension or changed behavior.
References:* AI Security Management™ (AAISM) Body of Knowledge: Human-centric Controls-Role- based training, policy-to-practice mapping, and scenario exercises for rapid risk reduction.* AI Security Management™ Study Guide: Awareness program design for generative AI misuse; behavior-anchored training outcomes.

質問 # 128
Which of the following MOST effectively secures ongoing stakeholder support for AI initiatives?

A. Conducting periodic staff training
B. Addressing and optimizing AI-related risk
C. Quantifying and communicating the value of AI solutions
D. Developing and monitoring an AI strategic roadmap

正解：C

解説：
AAISM governance guidance emphasizes that stakeholder buy-in is sustained when the measurable value of AI initiatives is clearly communicated. Value demonstrations include:
* improved efficiency
* reduced cost
* reduced risk
* business growth
Training (B) and risk optimization (C) are important but do not guarantee stakeholder support. A roadmap (D) guides planning but does not secure buy-in.
References: AAISM Study Guide - AI Governance; Stakeholder Engagement & Value Communication.

質問 # 129
Which of the following key risk indicators (KRIs) is MOST relevant when evaluating the effectiveness of an organization's AI risk management program?

A. Percentage of AI projects in compliance
B. Percentage of critical business systems with AI components
C. Number of AI-related training requests submitted
D. Number of AI models deployed into production

正解：A

解説：
AAISM identifies percentage of AI projects in compliance as the most relevant KRI for evaluating AI risk management effectiveness. This metric directly reflects adherence to governance, regulatory, and security requirements. The number of models deployed (A) or systems with AI components (B) indicate scale, not risk management quality. Training requests (D) show awareness levels but do not measure effectiveness of risk management. Compliance percentage provides a direct, measurable indication of how well risks are being governed and mitigated.
References:
AAISM Exam Content Outline - AI Risk Management (Risk Metrics and Compliance) AI Security Management Study Guide - Key Risk Indicators in AI Programs

質問 # 130
A retail organization implements an AI-driven recommendation system that utilizes customer purchase history. Which of the following is the BEST way for the organization to ensure privacy and comply with regulatory standards?

A. Establishing a governance committee to oversee AI privacy practices
B. Storing customer data indefinitely to ensure the AI model has a complete history
C. Conducting quarterly retraining of the AI model to maintain the accuracy of recommendations
D. Maintaining a register of legal and regulatory requirements for privacy

正解：D

解説：
According to the AI Security Management™ (AAISM) study framework, compliance with privacy and regulatory standards must begin with a formalized process of identifying, documenting, and maintaining applicable obligations. The guidance explicitly notes that organizations should maintain a comprehensive register of legal and regulatory requirements to ensure accountability and alignment with privacy laws. This register serves as the foundation for all governance, risk, and control practices surrounding AI systems that handle personal data.
Maintaining such a register ensures that the recommendation system operates under the principles of privacy by design and privacy by default. It allows decision-makers and auditors to trace every AI data processing activity back to relevant compliance obligations, thereby demonstrating adherence to laws such as GDPR, CCPA, or other jurisdictional mandates.
Other measures listed in the options contribute to good practice but do not achieve the same direct compliance outcome. Retraining models improves technical accuracy but does not address legal obligations. Oversight committees are valuable but require the documented register as a baseline to oversee effectively. Indefinite storage of customer data contradicts regulatory requirements, particularly the principle of data minimization and storage limitation.
AAISM Domain Alignment:
This requirement falls under Domain 1 - AI Governance and Program Management, which emphasizes organizational accountability, policy creation, and maintaining compliance documentation as part of a structured governance program.
References from AAISM and ISACA materials:
AAISM Exam Content Outline - Domain 1: AI Governance and Program Management AI Security Management Study Guide - Privacy and Regulatory Compliance Controls ISACA AI Governance Guidance - Maintaining Registers of Applicable Legal Requirements

質問 # 131
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テスト用のAAISM認定を準備する際に、AAISM試験リファレンスのように高い効率と合格率を高めることができる学習教材はありません。 AAISM試験の練習問題では、最も信頼性の高い試験情報リソースと最も認定された専門家の検証を提供しています。テストバンクには、実際の試験に含まれる可能性のあるすべての質問と回答、および過去の試験問題の本質と要約が含まれています。最も簡単な言語を使用して、学習者にAAISM試験の参照を理解させ、AAISM試験に合格するよう努めています。

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