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| Certification Vendor: | ISACA |
|---|---|
| Exam Name: | ISACA Advanced in AI Security Management (AAISM) Exam |
| Exam Number: | AAISM |
| Passing Score: | 450 (out of 800) |
| Real Exam Qty: | 90 |
| Certificate Validity Period: | 3 years |
| Exam Price: | US$459 (members), US$599 (non-members) |
| Exam Duration: | 150 minutes |
| Exam Format: | Scenario-based, Multiple-choice |
| Available Languages: | English |
| Related Certifications: | CISM CISSP |
| 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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問題 #69
When developing organizational generative AI policies, the FIRST step is to:
答案：D
解題說明：
Inventorying the current state of AI systems, use cases, and processes is the first step because an organization must understand where and how generative AI is being used before it can effectively define governance, assess risks, establish ethical expectations, or apply regulatory requirements.
問題 #70
A post-incident investigation finds that an AI-powered anti-money laundering system inadvertently allowed suspicious transactions because certain risk signals were disabled to reduce false positives. Which of the following governance failures does this BEST demonstrate?
答案：B
解題說明：
AAISM states that AI risk signals, thresholds, and model logic must be governed through strict validation and change control processes. Disabling key risk indicators without formal review or testing directly reflects a failure in:
- AI model validation
- Change management
- Governance oversight
問題 #71
Which of the following is the MOST important consideration when an organization is adopting generative AI for personalized advertising?
答案：D
解題說明：
In AAISM, usage of AI for activities involving personal data and profiling, such as personalized advertising, is explicitly mapped to stringent regulatory and compliance requirements (e.g., data protection, consent, profiling limitations, fairness obligations). The material notes that these activities may trigger "heightened regulatory scrutiny, mandatory impact assessments, and potential penalties for non-compliance."
問題 #72
Which of the following BEST describes an adversarial attack on an AI model?
答案：B
解題說明：
In AAISM, an adversarial attack is defined by maliciously crafted inputs designed to cause erroneous model behavior (misclassification, targeted misprediction) while the model architecture and parameters remain unchanged. Hardware compromise (A) and DoS (D) are system-level attacks, not adversarial ML per se.
Social engineering to obtain model information (C) is an information-gathering or security breach vector, distinct from input-space adversarial manipulation.
References:AI Security Management™ (AAISM) Body of Knowledge: Taxonomy of AI Threats- Adversarial Examples and Evasion; Distinction from System/Network Attacks.AAISM Study Guide:
Definitions and Threat Models in Adversarial ML; Attack-Defense Mapping for Model Predictions.
問題 #73
Which of the following involves documenting and monitoring the complete journey of data as it flows through an AI system?
答案：C
解題說明：
Data lineage records and monitors the end-to-end journey of data-sources, movements, transformations, storage locations, uses, and dependencies-providing traceability, auditability, and accountability across the AI lifecycle. "Origin" is a single point (provenance), "transformation" is one step within the flow, and
"processing" is a general activity rather than a governance record of the entire path.
References: AI Security Management (AAISM) Body of Knowledge: Data Governance-Provenance and Lineage; AAISM Study Guide: Lineage Documentation, Traceability, and Audit Evidence.
問題 #74
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