Isaca Certification Exams Pack
Everything from Basic, plus:
- Exam Name: ISACA Advanced in AI Security Management (AAISM) Exam
- 255 Questions Answers with Explanation Detail
- Total Questions: 255 Q&A's
- Single Choice Questions: 255 Q&A's
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Which of the following is the MOST critical key risk indicator (KRI) for an AI system?
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D
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Explanation
AAISM highlights that while accuracy and performance metrics are important, the rate of drift is the most critical KRI for AI systems. Model drift occurs when input data or environmental conditions shift, causing the system to degrade and produce unreliable outputs. This risk indicator directly reflects whether the AI continues to function as intended over time. Accuracy rates and response times are performance metrics, not primary risk signals. The amount of data in the model does not reliably indicate exposure to risk. Therefore, the greatest KRI for ongoing assurance and governance is the rate of drift. [References:, AAISM Study Guide – AI Risk Management (Monitoring and Drift Detection), ISACA AI Security Management – Key Risk Indicators for AI Systems, , ]
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Which of the following security framework elements BEST helps to safeguard the integrity of outputs generated by AI algorithms?
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A
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Explanation
According to AAISM technical controls, the element of security frameworks that directly safeguards output integrity is ensuring that bias-related risks are maintained within acceptable ranges. This ensures that AI results remain consistent, fair, and reliable, preserving trust in outputs. Ethical awareness, architectural disclosure, and legal responsibilities are governance practices but do not directly secure output integrity. Output integrity is primarily protected through bias management and ongoing evaluation of fairness and accuracy. [References:, AAISM Exam Content Outline – AI Technologies and Controls (Integrity of AI Outputs), AI Security Management Study Guide – Bias and Output Integrity Controls]
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Secure aggregation enhances the security of federated learning systems by:
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D
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Explanation
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. Option C (encryption in transit) is insufficient because decryption at the server reveals updates; Option A is procedural, not cryptographic; Option B (differential privacy) is a separate technique and not the defining property of secure aggregation. [References: AAISM Body of Knowledge: Privacy-Preserving ML—Federated Learning and Secure Aggregation; AAISM Study Guide: Threat Models for Aggregation Servers and Confidentiality Guarantees., ]
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Find answers to the most common questions about the Isaca AAISM exam, including what it is, how to prepare, and how it can boost your career.
The Isaca AAISM certification is a globally-acknowledged credential that is awarded to candidates who pass this certification exam by obtaining the required passing score. This credential attests and validates the candidates' knowledge and hands-on skills in domains covered in the Isaca AAISM certification syllabus. The Isaca AAISM certified professionals with their verified proficiency and expertise are trusted and welcomed by hiring managers all over the world to perform leading roles in organizations. The success in Isaca AAISM certification exam can be ensured only with a combination of clear knowledge on all exam domains and securing the required practical training. Like any other credential, Isaca AAISM certification may require periodic renewal to stay current with new innovations in the concerned domains.