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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.
What you’ll learn in this course
The AI+ Security Compliance is an advanced course that merges the fundamental principles of cybersecurity compliance with the transformative power of artificial intelligence (AI). Building on the CISSP framework, this course focuses on how AI can enhance compliance processes, improve risk management, and ensure robust security measures in alignment with regulatory standards.
This course introduces you to the core principles of cyber security compliances, while exploring the potential of AI to enhance your security posture. This course structure integrates comprehensive cybersecurity compliance principles with advanced AI applications, providing learners with the necessary skills to ensure compliance and enhance security through AI technologies.
Course Objectives
• Gain a thorough understanding of cybersecurity compliance with a focus on AI integration.
• Acquire knowledge of essential compliance frameworks and international standards.
• Learn how to develop and implement effective compliance programs.
• Explore AI's role in risk management and asset security.
• Investigate AI's applications in security architecture, network security, and software development.
• Examine emerging trends in AI and cybersecurity, including quantum computing and ethical considerations.
• Develop skills to implement and manage AI-driven security solutions effectively within organizations
Course Outline
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Further information
If you would like to know more about this course please contact us
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