Certified AI Cyber Defense Analyst (CACDA™)

Length: 2 Days

The Certified AI Cyber Defense Analyst (CACDA™) certification prepares individuals to effectively utilize AI technologies in cyber defense strategies. It focuses on the application of AI in detecting, analyzing, and responding to cyber threats, and on managing and improving cyber defense mechanisms.

Objectives:

• To understand the role of AI in enhancing cyber defense capabilities.
• To gain skills in using AI tools and techniques for threat detection and response.
• To develop proficiency in analyzing and mitigating cyber threats using AI-powered solutions.
• To enhance strategic thinking in integrating AI into cyber defense planning and operations.

Target Audience:

• Cybersecurity professionals looking to specialize in AI-driven cyber defense.
• IT security analysts and network administrators interested in AI applications in cybersecurity.
• Professionals in threat intelligence and incident response roles.
• Security operation center (SOC) personnel seeking to leverage AI in their workflows.

Certification Modules:

Module 1: Introduction to AI in Cyber Defense

• Fundamentals of AI and machine learning in cybersecurity.
• Overview of AI’s impact on threat detection, analysis, and response.

Module 2: AI-Driven Threat Intelligence

• Utilizing AI to gather, analyze, and interpret threat intelligence.
• Techniques for proactive threat hunting and anomaly detection using AI.

Module 3: AI in Network and Endpoint Security

• Implementing AI-driven solutions for network and endpoint security.
• Strategies for automating response and mitigation actions with AI technologies.

Module 4: Incident Response and AI

• Integrating AI tools in incident response workflows.
• Enhancing incident analysis and decision-making through AI.

Module 5: AI in Security Operations Center (SOC)

• Role of AI in SOC operations and threat management.
• Leveraging AI for improved situational awareness and response efficiency.

Module 6: Ethical and Legal Considerations of AI in Cyber Defense

• Addressing ethical concerns and legal issues related to the use of AI in cybersecurity.
• Ensuring privacy and compliance in AI-driven security operations.

Module 7: Case Studies and Practical Applications

• Real-world examples of AI applications in cyber defense.
• Hands-on exercises and simulations to apply AI in various cybersecurity scenarios.

Module 8: Certification Exam Preparation

• Comprehensive review of AI applications in cyber defense.
• Practice tests and scenario-based exercises to prepare for the certification exam.

Exam Domains:

1. Introduction to AI in Cyber Defense:
   • Understanding AI concepts
   • AI applications in cybersecurity
   • Ethics and challenges in AI-driven cyber defense
2. Machine Learning Fundamentals:
   • Supervised learning
   • Unsupervised learning
   • Reinforcement learning
   • Deep learning
3. Cyber Threat Intelligence and Analysis:
   • Threat intelligence gathering techniques
   • Threat modeling and classification
   • Analyzing threat actor behaviors using AI
4. AI in Intrusion Detection and Prevention:
   • AI-driven intrusion detection systems (IDS)
   • Intrusion prevention systems (IPS) with AI capabilities
   • Anomaly detection using machine learning algorithms
5. AI in Malware Detection and Analysis:
   • Malware detection techniques using AI
   • Behavioral analysis of malware with machine learning
   • Identifying and classifying malware families using AI
6. AI in Network Security:
   • AI-driven network security solutions
   • Network traffic analysis using machine learning
   • AI-powered network anomaly detection
7. AI in Endpoint Security:
   • Endpoint protection platforms (EPP) with AI features
   • Machine learning for endpoint threat detection
   • AI-driven endpoint security strategies
8. AI in Security Operations and Incident Response:
   • AI-enabled security orchestration, automation, and response (SOAR)
   • Incident response automation using AI
   • AI-driven security analytics for incident investigation

Question Types:

• Multiple choice questions assessing conceptual understanding.
• Scenario-based questions requiring analysis and application of AI in cyber defense.
• Practical questions involving the use of AI tools and techniques to solve security challenges.
• Essay questions exploring the ethical considerations of AI in cyber defense.

Passing Criteria:

• A passing score of 70% or higher.
• Demonstration of proficiency across all exam domains.
• Completion of practical exercises demonstrating practical application of AI in cyber defense.
• Submission of any required essays or written responses meeting specified criteria.