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NEW QUESTION # 323
Security and assurance requirements for AI systems should FIRST be embedded in the:
Answer: B
Explanation:
AAISM directs organizations to embed security, safety, and compliance controls at design time ("secure-by- design" and "shift-left"), ensuring requirements for robustness, privacy, and governance are defined as non- functional constraints on architecture, data sourcing, model choices, and evaluation criteria before any model is trained. Deferring these requirements to training, testing, or deployment increases residual risk and rework, and weakens traceability of control coverage.
References:* AI Security Management™ (AAISM) Body of Knowledge: Governance-Secure-by-Design; Policy-to-Control Traceability; Requirements Management* AAISM Study Guide: AI Program Lifecycle- Planning & Design Controls; Design-time Threat Modeling and Control Selection* AAISM Mapping to Standards: Design-phase Risk Identification and Requirements Engineering for AI
NEW QUESTION # 324
Which of the following is the MAIN objective of the operational phase of AI life cycle management?
Answer: D
Explanation:
AAISM identifies the operational phase as the stage where the AI system is actively deployed and requires continuous monitoring of performance, drift, security, and reliability.
Business alignment (B) belongs to planning and design. Optimization (A) and user feedback (D) are part of development or improvement cycles, not primary operational objectives.
References: AAISM Study Guide - AI Life Cycle Management; Operational Monitoring Requirements.
NEW QUESTION # 325
Which of the following is MOST important for an organization to consider when implementing a preventive security safeguard into a new AI product?
Answer: C
Explanation:
AAISM materials emphasize that the most effective preventive safeguard is to ensure input sanitization. Preventive controls stop malicious or malformed inputs from reaching the model in the first place, thereby reducing the likelihood of prompt injection, evasion, or poisoning at inference time. Model output monitoring is a detective control, not preventive. Penetration testing is an assessment technique rather than a safeguard. Differential privacy protects data privacy but does not prevent adversarial input manipulation. Therefore, the most important preventive safeguard in a new AI product is robust input sanitization.
NEW QUESTION # 326
Which of the following is the GREATEST threat to an organization where shadow generative AI is prevalent?
Answer: A
Explanation:
Shadow generative AI often operates outside governance and security controls, increasing the likelihood that sensitive or proprietary information is entered into uncontrolled systems, leading to unintended exposure or data leakage.
NEW QUESTION # 327
Which of the following should be the PRIMARY objective of implementing differential privacy techniques in AI models leveraging fraud detection systems?
Answer: A
Explanation:
Differential privacy aims to protect the privacy of any single individual's data contribution while still enabling useful aggregate learning and statistical analysis. Noise mechanisms are calibrated so that results remain informative for modeling (e.g., fraud patterns) without revealing whether any particular person's data was included or enabling inference about them. Accuracy, speed, and compute efficiency can be secondary considerations, but the primary objective is privacy protection with utility preserved.
References: AI Security Management™ (AAISM) Body of Knowledge: Privacy-Preserving ML; Differential Privacy Objectives and Mechanisms. AAISM Study Guide: Individual Contribution Protection; Utility- Privacy Trade-offs and Calibration in Applied Models.
NEW QUESTION # 328
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