Exam CY0-001 Discount, Simulation CY0-001 Questions

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CompTIA CY0-001 Exam Syllabus Topics:

SectionWeightObjectives
Basic AI Concepts Related to Cybersecurity17%- AI-driven threats and risks
  • 1. Adversarial machine learning attacks
  • 2. Malicious use of generative AI
  • 3. Automated phishing, polymorphic malware
- AI applications in security
  • 1. Security automation and decision support
  • 2. Threat detection and anomaly analysis
- Core AI principles and terminology
  • 1. Generative AI concepts and capabilities
  • 2. Machine learning, deep learning, NLP, automation
AI Governance, Risk and Compliance19%- Governance frameworks and policies
  • 1. Global standards: NIST AI RMF, EU AI Act
  • 2. Responsible AI principles and ethics
  • 3. Organizational AI governance structures
- Compliance and legal requirements
  • 1. Data protection and privacy laws
  • 2. Transparency, accountability and auditability
- Risk management for AI
  • 1. Risk mitigation and control strategies
  • 2. AI risk identification and assessment
Securing AI Systems40%- Security controls for AI systems
  • 1. Deployment environment security
  • 2. Model security: access, integrity, anti-tampering
  • 3. Data protection: integrity, confidentiality, privacy
- Secure AI development and operations
  • 1. DevSecOps integration for AI
  • 2. Secure MLOps and AI pipeline design
- Defending against AI-specific attacks
  • 1. Threat modeling for AI lifecycles
  • 2. Prompt injection, data poisoning, model inversion
  • 3. Adversarial example defense
AI-assisted Security24%- AI in security strategy and operations
  • 1. Compliance monitoring and auditing
  • 2. Threat modeling and risk assessment
- Security automation and orchestration
  • 1. Vulnerability management and assessment
  • 2. Workflow automation and response playbooks
- AI for threat detection and response
  • 1. Automated incident triage and correlation
  • 2. Anomaly detection and behavioral analysis
  • 3. Accelerated threat hunting

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CompTIA SecAI+ Certification Exam Sample Questions (Q89-Q94):

NEW QUESTION # 89
A security administrator needs to improve an AI model. During an initial investigation, the administrator notices that two successive login features are recorded every day, and then a successful login occurs after a specific time interval. All the successful login attempts have been during office hours.
Which of the following techniques should the administrator use to improve the AI model's security?

Answer: D

Explanation:
The administrator is analyzing repeated login behaviors and time-based patterns that precede successful access. Pattern recognition allows the AI model to detect these behavioral trends, improving its ability to identify anomalies or potential attacks while aligning with normal office-hour login behavior.


NEW QUESTION # 90
An automobile manufacturer implements a chatbot to assist with configuration options for customer automobiles. Given a customer ' s prompt, the chatbot gives offensive responses.
Which of the following describes this behavior?

Answer: B


NEW QUESTION # 91
A security architect performs threat modeling of an AI system. The architect needs to determine which attacks can be performed against the system.
Which of the following actions should the architect take next?

Answer: C

Explanation:
MITRE ATLAS is specifically designed to catalog adversarial TTPs targeting AI systems. By analyzing ATLAS, the architect can determine which types of attacks are possible against the AI system, making it the most appropriate resource for threat modeling in this context.


NEW QUESTION # 92
An organization is developing and implementing AI features into a customer service application.
Which of the following practices should the organization put the place before releasing the application for customer trials?

Answer: D

Explanation:
Before releasing AI features for customer trials, it is critical to protect sensitive information that may be used during testing. Data masking and sanitization ensure customer or corporate data is anonymized or obfuscated, reducing the risk of data exposure while still allowing realistic evaluation of the AI system.


NEW QUESTION # 93
A developer is proposing a new AI application for human resources systems. Which of the following are the most important considerations?

Answer: C

Explanation:
Option B is correct because a human resources AI application processes highly sensitive employee and applicant information and may influence consequential employment decisions. Privacy and security therefore determine whether the system can be deployed responsibly. The design must address data minimization, lawful collection, access control, encryption, retention, auditability, secure model integration, and protection against unauthorized disclosure. It should also evaluate whether training data or outputs expose protected or confidential information and whether human review is required before decisions affect candidates or employees. Option A concerns friendliness and presentation, not the protection of people or organizational data. Option C may improve usability, but visual design cannot compensate for insecure handling of resumes, performance records, or identity data. Option D can make outputs easier to consume, yet brevity and summarization do not control privacy risk or system compromise. The NIST AI Risk Management Framework identifies privacy enhancement, security, resilience, accountability, and transparency as characteristics of trustworthy AI, making privacy and security the controlling considerations in this scenario.


NEW QUESTION # 94
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