ISACA AAISM練習問題 & AAISM認定資格試験問題集

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ISACA AAISM Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Technologies and Controls38%- AI Assurance and Safety
  • 1. Bias mitigation
    • 2. Model validation and testing
      • 3. Ethical AI controls
        - AI Security Architecture
        • 1. Secure AI system design
          • 2. Model lifecycle security
            - Data and Model Controls
            • 1. Data protection and governance
              • 2. Privacy-preserving techniques
                • 3. Monitoring and runtime controls
                  Topic 2: AI Governance and Program Management31%- AI Strategy and Policy
                  • 1. Responsible and acceptable use
                    • 2. AI strategy development
                      • 3. Policies and procedures
                        - Frameworks and Compliance
                        • 1. Privacy and ethics considerations
                          • 2. Regulatory requirements
                            • 3. Industry frameworks and standards (e.g., NIST AI RMF, ISO/IEC 42001)
                              - AI Governance Foundations
                              • 1. Roles and responsibilities
                                • 2. Stakeholder considerations
                                  • 3. Organizational structure and governance
                                    Topic 3: AI Risk Management31%- AI Threats and Vulnerabilities
                                    • 1. Data poisoning and model manipulation
                                      • 2. Supply chain and vendor risks
                                        • 3. Adversarial AI and ML attacks
                                          - AI Risk Assessment
                                          • 1. Risk identification and analysis
                                            • 2. Risk thresholds and treatment

                                              >> ISACA AAISM練習問題 <<

                                              AAISM試験の準備方法｜信頼的なAAISM練習問題試験｜有難いISACA Advanced in AI Security Management (AAISM) Exam認定資格試験問題集

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                                              ISACA Advanced in AI Security Management (AAISM) Exam 認定 AAISM 試験問題 (Q181-Q186):

                                              質問 # 181
                                              An organization is looking to purchase an AI application from a vendor but is concerned about the security of its data. Which of the following is the MOST effective way to address this concern?

                                              正解：A

                                              解説：
                                              AAISM's approach to third-party and vendor risk for AI systems stresses data usage transparency as a primary control. The guidance explains that organizations must obtain clear documentation on "what data is collected, how it is processed, stored, retained, and whether it is reused for training or shared with other parties." Option C directly addresses this by requiring the vendor to disclose how the application uses organizational data, enabling appropriate risk assessment, contractual controls, and technical safeguards. An external audit (A) can be useful but may be costly and not always feasible pre-procurement. Legal discussions (B) are important but ineffective without clarity on data flows. Publicly available policies (D) are often high- level and marketing-oriented, lacking the specificity required for proper risk evaluation. Therefore, obtaining explicit data usage disclosures from the vendor is the most effective starting point.
                                              References: AI Security Management™ (AAISM) Study Guide - Third-Party AI Risk and Data Sharing; Vendor Governance Requirements.


                                              質問 # 182
                                              Secure aggregation enhances federated learning security by:

                                              正解：B

                                              解説：
                                              AAISM explains that secure aggregation ensures the server only sees aggregated model updates--not individual client contributions--so privacy is preserved even if the server is breached.


                                              質問 # 183
                                              Which of the following is MOST important to monitor in order to ensure the effectiveness of an organization's AI vendor management program?

                                              正解：B

                                              解説：
                                              The AAISM framework specifies that the primary metric of effectiveness in vendor management is the vendor's compliance with AI-related requirements defined in contracts and governance frameworks. This provides measurable assurance that vendors adhere to agreed-upon privacy, security, and ethical standards. Reviews of threat reports, training results, or research participation are supplemental and may support continuous improvement, but they do not establish compliance accountability. Governance requires a direct focus on whether contractual and regulatory obligations are being fulfilled. Therefore, vendor compliance with AI requirements is the most important monitoring focus.


                                              質問 # 184
                                              Which phase of the AI data life cycle presents the GREATEST inherent risk?

                                              正解：A

                                              解説：
                                              AAISM identifies training as the phase with the highest inherent risk because this is where:
                                              * data poisoning can occur
                                              * sensitive data may be exposed
                                              * bias can be introduced
                                              * model inversion risks originate
                                              * security and privacy vulnerabilities are embedded
                                              Preparation (C) carries risk but is less critical. Maintenance (B) and monitoring (A) involve operational safeguards, not foundational risk creation.
                                              References: AAISM Study Guide - AI Data Life Cycle Risks; High-Risk Model Training Phase.


                                              質問 # 185
                                              Which of the following BEST helps an organization protect confidential data while using a pre- trained open-source AI solution?

                                              正解：C

                                              解説：
                                              Verifying and sanitizing inputs prevents sensitive data from being unintentionally exposed to the model, while sanitizing outputs helps ensure that confidential information is not leaked in responses, directly protecting data during use.


                                              質問 # 186
                                              ......

                                              この分野には多くの専門家や教授がいます。すべての人々の要求を満たすために、当社のこれらの優秀な専門家および教授は昼夜を問わず働いています。彼らはすべての人々のために当社から最高のAAISM認定トレーニング教材を設計するために最善を尽くしました。学習資料により、すべての人がより効率的な方法でAAISM試験の準備をすることができます。 AAISM学習教材がすべての人々に適し、学生、労働者、主婦などすべての人々の要求を満たすことを保証できます。

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