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NEW QUESTION # 94
An attacker is able to exploit the intended behavior of an AI system using a specific input or classes of inputs. Which type of attack is this an example of?
Answer: B
Explanation:
An evasion attack occurs when an attacker crafts specific inputs designed to exploit the AI system during operation, causing the model to produce incorrect or unintended behavior while still functioning within its deployed environment.
NEW QUESTION # 95
The PRIMARY purpose of adopting and implementing AI architecture as part of an organizational AI program is to:
Answer: D
Explanation:
An AI architecture, within program governance, exists to align AI system components and lifecycle processes with business goals and policy constraints. Architecture provides the organizing structure linking strategy, capabilities, processes, data, models, controls, and assurance so that AI outcomes are traceable to business value, risk appetite, and compliance expectations. Efficiency, speed, and threat analysis are important architectural qualities, but they are not the primary purpose; the primary purpose is strategic and governance alignment so that technical choices and controls consistently realize organizational objectives.
References:* AI Security Management (AAISM) Body of Knowledge: AI Program Architecture - alignment of capabilities, processes, and controls to business objectives* AI Security Management Study Guide: Architecture-driven governance, traceability from business goals to technical and control design
NEW QUESTION # 96
After an organization deploys an AI-based system, a regulator warns of increased risk related to AI re-identification attacks on anonymized datasets. Which of the following should the information security manager do FIRST?
Answer: A
Explanation:
Establishing continuous monitoring with privacy audits and adversarial testing directly addresses the evolving risk of re-identification by detecting vulnerabilities and measuring the effectiveness of anonymization over time. This proactive approach enables the organization to assess and mitigate the risk without unnecessarily disrupting operations.
NEW QUESTION # 97
Which area of intellectual property law presents the GREATEST challenge in determining copyright protection for AI-generated content?
Answer: A
Explanation:
AAISM governance content highlights that the greatest intellectual property challenge in the context of AI- generated works is determining rightful ownership. Traditional copyright law requires human authorship, but AI-generated creations blur authorship and ownership boundaries, raising legal uncertainty about who can claim rights. Trademark enforcement, trade secret protection, and licensing frameworks are established areas of IP law but do not present the same fundamental challenge as ownership attribution. For AI-generated content, the central legal dilemma is ownership of the creation.
References:
AAISM Study Guide - AI Governance and Program Management (Intellectual Property and AI) ISACA AI Security Management - Copyright and Ownership Challenges
NEW QUESTION # 98
An attack has occurred on an AI system that has been in use for two years. Which of the following would BEST mitigate the impact of the attack?
Answer: B
Explanation:
When an AI system experiences an attack after being in production for an extended period, the most effective mitigation strategy is to update the deployed training data with new adversarial data. This process strengthens the model's resilience by retraining it to recognize and resist attack vectors that were previously unknown or unaccounted for. According to the AI Security Management™ (AAISM) framework, risk mitigation for AI systems must address model robustness through adversarial retraining, data quality improvement, and model lifecycle hardening rather than relying solely on reactive measures.
Why Option B is Correct:
* Incorporating adversarial examples into the training set enhances the system's ability to correctly classify and withstand malicious inputs.
* This approach directly mitigates the vulnerability exploited in the attack and supports a proactive, continuous risk management cycle.
Why Other Options Are Incorrect:
* Option A: Monitoring helps detect suspicious activity but does not resolve the underlying vulnerability.
* Option C: Concealing confidence scores may reduce model transparency but does not address the attack mechanism or its root cause.
* Option D: Implementing access controls protects the model's architecture but does not improve model robustness against input manipulation attacks.
Exact Extract from Official AAISM Study Guide:
"AI risk management requires continuous improvement following incidents. After an adversarial or data poisoning event, the preferred risk treatment involves retraining the model using adversarial data and updated datasets to enhance robustness. This ensures the AI model adapts to evolving threat landscapes rather than merely restricting access or obscuring outputs." References:
AI Security Management™ (AAISM) Body of Knowledge: AI Risk Treatment and Mitigation Strategies, Adversarial Robustness and Resilience Engineering.
AI Security Management™ Study Guide: Model Lifecycle Security, Continuous Risk Treatment through Adversarial Retraining.
ISO/IEC 23894:2023, Clause 8.3.2 - Risk treatment through robustness improvement and adversarial data inclusion.
NEW QUESTION # 99
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