無料でクラウドストレージから最新のShikenPASS AAISM PDFダンプをダウンロードする：https://drive.google.com/open?id=1TIvqRQYqfnjHGHNkpq2cHQQAjdKUH5_D
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ShikenPASSが提供した問題集をショッピングカートに入れて100分の自信で試験に参加して、成功を楽しんで、一回だけISACAのAAISM試験に合格するのが君は絶対後悔はしません。
質問 # 229
Which of the following factors is MOST important for preserving user confidence and trust in generative AI systems?
正解：C
解説：
AAISM risk guidance underscores that transparent disclosure and informed consent are the most important factors in maintaining user trust in generative AI. Users must clearly understand how outputs are created, what data sources are used, and how risks such as bias or misinformation are managed. While bias minimization, access controls, and anonymization contribute to technical or ethical robustness, they are not sufficient to preserve user trust. Trust requires openness and consent, which align with governance expectations for transparency and accountability.
質問 # 230
Which of the following BEST describes an adversarial attack on an AI model?
正解：A
解説：
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.
質問 # 231
When addressing privacy concerns related to AI systems, which of the following is the GREATEST significance of user consent for an organization?
正解：D
解説：
Within AAISM's privacy governance, consent is a lawful basis that authorizes processing of personal data for defined purposes. Its principal significance is granting the organization the authority to process user data in AI workflows in line with stated purposes and limits.
質問 # 232
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?
正解：D
解説：
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.
質問 # 233
An organization engages its end users to be involved in the AI life cycle to validate security controls. Which of the following MOST effectively supports decision-making regarding ethical and safety controls?
正解：B
解説：
Providing context and understanding potential risk enables end users to make informed judgments about how AI systems may impact safety and ethics in real-world scenarios, directly supporting effective decision-making for appropriate controls.
質問 # 234
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無料でクラウドストレージから最新のShikenPASS AAISM PDFダンプをダウンロードする：https://drive.google.com/open?id=1TIvqRQYqfnjHGHNkpq2cHQQAjdKUH5_D