🔒 Module 9 of 12

AI in Cybersecurity &
Forensic Readiness

Master the dual role of AI in security: as a powerful defensive tool and as a system requiring protection. Learn AI-specific threat vectors, incident response, and forensic investigation techniques.

📚 5 Parts + Quiz
12-15 Hours
🎓 Advanced Level
💻 Hands-On Focus

Learning Objectives

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AI-Powered Security

Understand how AI enhances threat detection, anomaly identification, and automated response capabilities in modern security operations.

AI-Specific Threats

Identify unique attack vectors targeting AI systems including adversarial attacks, data poisoning, model extraction, and prompt injection.

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Securing AI Systems

Apply security frameworks and controls specifically designed to protect AI models, training pipelines, and inference systems.

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AI Incident Response

Develop and execute incident response plans tailored for AI-specific security events and model compromises.

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AI Forensics

Conduct forensic investigations involving AI systems, preserving evidence and analyzing AI-related security incidents.

Legal Considerations

Navigate the legal and regulatory requirements for AI security, including evidence handling and compliance obligations.

Module Content

Key Frameworks & Standards

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NIST AI RMF

AI Risk Management Framework for identifying and mitigating AI security risks

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MITRE ATLAS

Adversarial Threat Landscape for AI Systems - knowledge base of AI attack techniques

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OWASP ML Top 10

Top security risks in machine learning applications

ISO/IEC 27001

Information security management system applicable to AI systems

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EU AI Act Security

Security requirements for high-risk AI systems under EU regulation

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NIST SP 800-86

Guide to integrating forensic techniques applicable to AI investigations

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Ready to Begin?

Start with Part 1 to learn how AI is transforming cybersecurity operations and threat detection.

Start Part 1