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We even guarantee our customers that they will pass CompTIA CY0-001 exam easily with our provided study material and if they failed to do it despite all their efforts they can claim a full refund of their money (terms and conditions apply). The third format is the desktop software format which can be accessed after installing the software on your Windows computer or laptop. The CompTIA SecAI+ Certification Exam (CY0-001) has three formats so that the students don't face any serious problems and prepare themselves with fully focused minds.
| Section | Weight | Objectives |
|---|---|---|
| Basic AI Concepts Related to Cybersecurity | 17% | - AI Threat Landscape
|
| AI Governance, Risk, and Compliance | 19% | - AI Governance Frameworks
|
| AI-Assisted Security | 24% | - Security Operations Enhancement
|
| Securing AI Systems | 40% | - Adversarial Defense
|
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NEW QUESTION # 161
Which IR document defines who must be contacted during a breach and within what timeframe?
Answer: B
Explanation:
The communications plan specifies notification roles and timelines.
NEW QUESTION # 162
Which of the following helps in managing potential security issues related to model training?
Answer: A
Explanation:
The NIST AI RMF provides structured guidance for identifying, assessing, and managing risks specific to AI systems, including those arising during model training. It addresses issues like bias, security, and data integrity, making it the best framework for managing training-related security concerns.
NEW QUESTION # 163
Which of the following corporate policies would a security architect most likely reference when configuring an AI system to conduct input filtering?
Answer: D
Explanation:
Data governance is the most relevant corporate policy because input filtering depends on knowing what information may enter the AI system, how that information is classified, and which categories of sensitive or regulated data must be blocked, redacted, masked, or otherwise controlled. CompTIA SecAI+ specifically includes sensitive data governance under corporate AI policies and separately identifies data classification labels, redaction, masking, minimization, and related data-safety controls. A security architect can therefore translate the organization ' s data governance rules into technical input-filtering requirements, such as preventing credentials, customer PII, financial information, confidential intellectual property, or restricted datasets from being submitted to a model. A public-model usage policy governs whether and how employees may use externally hosted models, but it is narrower than the underlying data-handling rules. Third-party compliance evaluates external providers and contractual or regulatory obligations. Terms of use describe permitted user behavior but normally do not provide the detailed data-classification requirements required to implement technical filtering. Data governance is therefore the authoritative basis for determining what input the AI system should accept or reject.
NEW QUESTION # 164
An AI-based human resources system screens resumes to select the most suitable candidate for an interview.
The system recommends mostly male candidates. Which of the following responsible AI concepts does this system violate?
Answer: C
Explanation:
Fairness is the responsible AI principle most clearly violated because the system is producing a disproportionately gender-skewed outcome in a consequential employment decision. CompTIA SecAI+ explicitly identifies fairness as a responsible AI consideration and identifies the introduction of bias as an AI risk. A resume-screening system should evaluate candidates using relevant employment criteria without systematically disadvantaging a protected or unrelated demographic group. Recommending mostly male candidates signals a potential bias in the training data, feature selection, historical examples, model design, or decision threshold and therefore requires fairness assessment and mitigation. Transparency concerns whether stakeholders have appropriate visibility into how the AI system operates. Explainability concerns whether individual decisions can be described in understandable terms. Reliability concerns whether the system performs consistently and safely according to its intended specifications. Those properties remain important, but none directly describes the demographic disparity presented in the scenario. Because the evidence specifically indicates unequal treatment or outcomes between demographic groups, fairness is the responsible AI principle most directly implicated.
NEW QUESTION # 165
A global security operations center (SOC) wants to adapt and leverage the strength of AI in order to enhance its security operations. Which of the following is the best way to enhance the global SOC functions?
Answer: A
Explanation:
AI can significantly enhance SOC operations by summarizing and correlating high volumes of alerts, enabling analysts to quickly identify patterns, prioritize threats, and gain actionable insights. This reduces analyst fatigue and improves response times without introducing unsafe automation risks.
NEW QUESTION # 166
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