AAISM考試備考經驗，AAISM學習筆記

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ISACA AAISM Exam Syllabus Topics:

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

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最新的 ISACA AAISM Certification AAISM 免費考試真題 (Q128-Q133):

問題 #128
Which of the following controls BEST mitigates the risk of data poisoning?

答案：A

解題說明：
The AAISM technical controls framework emphasizes data validation as the primary safeguard against data poisoning attacks. Poisoning occurs when attackers insert malicious or corrupted data into training sets. Validation techniques verify the quality, authenticity, and consistency of input data before training, preventing compromised samples from corrupting the model.
Restoration helps after compromise, watermarking protects ownership, and intrusion detection monitors networks rather than data quality. The most effective preventive measure is data validation.


問題 #129
A critical AI system shows biased outcomes. What is the BEST course of action?

答案：B

解題說明：
AAISM emphasizes root cause analysis as the primary step when AI behavior deviates unexpectedly. RCA determines whether issues stem from:
* data drift
* model drift
* poisoned data
* missing features
* logic errors
* configuration changes
Retraining (D) may be required later, but only after RCA. Kill switches (A) are last-resort tools. Audits (B) help but are narrower than RCA.
References: AAISM Study Guide - Incident Response for AI; Root Cause First Principle.


問題 #130
Which of the following BEST describes how supervised learning models help reduce false positives in cybersecurity threat detection?

答案：A

解題說明：
According to AAISM technical content, supervised learning models reduce false positives by learning from historical labeled data that distinguishes between legitimate activity and actual threats. This training enables the model to recognize patterns and improve its discrimination ability over time. Grouping patterns (A) describes clustering, an unsupervised method. Real-time feature engineering (B) and generating new labeled data (D) are advanced techniques but not the fundamental supervised learning approach. The essence of supervised learning is leveraging labeled data to minimize misclassification, including false positives.
References:
AAISM Exam Content Outline - AI Technologies and Controls (Machine Learning Approaches) AI Security Management Study Guide - Supervised Learning for Threat Detection


問題 #131
An organization is adopting an agentic AI solution from an external vendor to support its internal IT operations. To evaluate the security posture of this system, which of the following provides the MOST reliable and independently verifiable evidence of implemented security controls?

答案：A

解題說明：
Third-party audit reports provide independent assurance that the vendor's stated controls are designed and operating effectively against recognized criteria. Such attestations (e.g., audit/assurance frameworks) are traceable, repeatable, and verifiable, and they support supply- chain risk reviews and contractual assurance. Internal red-team reports are not independent, industry "peer reviews" are not control attestations, and whitepapers are marketing/educational materials without evidence of control operation.


問題 #132
Which of the following should be the MOST important consideration when conducting an AI impact assessment?

答案：C

解題說明：
AAISM defines an AI Impact Assessment (AIIA) as a structured evaluation designed to determine whether an AI system can safely and responsibly support business objectives without creating unacceptable risks.
The framework states that alignment to business objectives is the central purpose of AI adoption and therefore must be the starting point in an impact assessment.


問題 #133
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