AI+ Security Compliance

Prerequisites

• Basic understanding of cybersecurity principles.
• Knowledge of networking fundamentals.
• Familiarity with programming concepts and languages (Python recommended)
• An introductory course on AI or machine learning is beneficial but not required.

Course outline

1. 1

   Lesson 1: Introduction to Cybersecurity Compliance and AI

   • 1.1 Overview of Cybersecurity Compliance
   • 1.2 International Compliance Standards
   • 1.3 Developing Compliance Programs
   • 1.4 Implementing Compliance Programs
   • 1.5 AI in Cybersecurity Compliance
   • 1.6 Case Studies and Applications
2. 2

   Lesson 2: Security and Risk Management with AI

   • 2.1 Risk Management Frameworks
   • 2.2 Conducting Risk Assessments
   • 2.3 AI in Risk Assessment
   • 2.4 Compliance and AI
   • 2.5 Incident Response and AI
3. 3

   Lesson 3: Asset Security and AI for Compliance

   • 3.1 Data Classification and Protection
   • 3.2 AI in Privacy Protection
   • 3.3 Asset Management with AI
   • 3.4 Case Studies and Best Practices
4. 4

   Lesson 4: Security Architecture and Engineering with AI

   • 4.1 Secure Design Principles
   • 4.2 AI in Cryptography
   • 4.3 AI in Vulnerability Assessment
   • 4.4 Security Models and AI
5. 5

   Lesson 5: Communication and Network Security with AI

   • 5.1 Network Security Fundamentals
   • 5.2 AI in Network Monitoring
   • 5.3 AI-driven Network Defense
   • 5.4 Compliance in Network Security
6. 6

   Lesson 6: Identity and Access Management (IAM) with AI

   • 6.1 IAM Fundamentals
   • 6.2 AI in Identity Verification
   • 6.3 Access Control and AI
   • 6.4 Threats to IAM and AI Solutions
7. 7

   Lesson 7: Security Assessment and Incident Response with AI

   • 7.1 Security Testing Techniques
   • 7.2 AI in Security Testing
   • 7.3 Continuous Monitoring and AI
   • 7.4 Incident Response Planning
   • 7.5 Managing Cybersecurity Incidents
   • 7.6 Legal and Regulatory Considerations
8. 8

   Lesson 8: Security Operations with AI

   • 8.1 Security Operations Center (SOC)
   • 8.2 Data Classification and Protection
   • 8.3 Privacy Compliance
   • 8.4 Disaster Recovery and AI
   • 8.5 AI in Security Orchestration
9. 9

   Lesson 9: Software Development Security and Audit with AI

   • 9.1 Secure Software Development Life Cycle (SDLC)
   • 9.2 AI in Application Security Testing
   • 9.3 AI in Secure DevOps
   • 9.4 Threat Modeling and AI
   • 9.5 Internal and External Audits
   • 9.6 Continuous Monitoring
10. 10

    Lesson 10: Future Trends in AI and Cybersecurity Compliance

    • 10.1 Emerging AI Technologies
    • 10.2 AI in Cyber Threat Intelligence
    • 10.3 Quantum Computing and AI
    • 10.4 Ethical Considerations and AI Governance
    • 10.5 Practical Applications