AAISM Success Toolkit: 50-Day ISACA AAISM Exam Preparation Guide

Inside the book

About this book

AAISM Success Toolkit is a structured 50-day preparation guide for the ISACA Advanced in AI Security Management (AAISM) certification exam, written by Manoj Sharma, CISSP, CISM, CRISC and AAISM. The book is designed especially for experienced cybersecurity, risk, governance and information security professionals who understand security management but may be new to artificial intelligence. Instead of treating you like a beginner in cybersecurity, the book focuses on the AI-specific knowledge you need for AAISM and connects it to concepts you already understand: governance, accountability, risk appetite, data protection, security controls, assurance, vendor management and compliance. The 50-day roadmap covers all three AAISM domains: Domain 1 — AI Governance and Program Management Learn AI governance, organizational readiness, roles and responsibilities, standards and frameworks, AI strategy, policies and procedures, ethical AI, data governance, AI asset management and security programme development. Domain 2 — AI Risk Management Build a practical understanding of AI risk identification, risk frameworks, risk classification, risk response, threat modelling, AI-specific attacks and vulnerabilities, supply-chain risk, third-party AI and shared responsibility. Domain 3 — AI Technologies and Controls Understand the AI and machine-learning concepts security managers actually need, including models, neural networks, algorithms, AI architecture, the AI lifecycle, TEVV, deployment, monitoring, privacy, safety and security controls. The book includes day-by-day learning, Exam Focus sections, Quick Recall revision, “Easy to Confuse” comparisons, Exam Trap Alerts, key terminology, practical artifacts, management scenarios, domain revision days and a final exam sprint with five mock exams. Coach Manoj explains difficult AI concepts in plain language and continually connects them back to the decisions an AI security manager is expected to make. This is not a technical AI-development textbook. It is an exam-preparation and practical management guide for security professionals preparing to govern and secure AI. Free supporting study resources and practice material are also available through Cybernous.

Who this book is for

Ideal for cybersecurity and information security professionals preparing for the ISACA AAISM certification, including CISOs, security managers, security architects, risk managers, GRC professionals, auditors, consultants, privacy professionals, IT leaders and experienced CISSP, CISM, CISA, CRISC or similar certification holders. This book is especially useful if you already understand cybersecurity, governance and risk management but need a clear, structured introduction to AI governance, AI risk, machine learning concepts and AI security controls. No data science, machine-learning development or programming background is required.

What you will learn

• Understand the complete ISACA AAISM exam syllabus across all three domains
• Explain AI governance, accountability, organizational readiness and risk appetite
• Differentiate AI governance, management, provider, deployer and stakeholder responsibilities
• Understand AI standards, frameworks, regulations and responsible AI principles
• Evaluate AI use cases, strategy, policies, procedures and build-versus-buy decisions
• Identify and manage AI assets, models, datasets and data governance requirements
• Understand AI risk frameworks, risk classification and appropriate risk responses
• Recognize AI-specific threats, vulnerabilities and attack techniques
• Assess third-party AI, supply-chain risk and shared-responsibility boundaries
• Understand machine learning, models, neural networks and algorithms at a security-manager level
• Understand the AI lifecycle from design and development through deployment, monitoring and retirement
• Apply TEVV, privacy, ethics, trust, safety and security controls to AI systems
• Think through AAISM scenarios from the perspective of an accountable AI security manager
• Recognize common AAISM exam traps and distinguish easily confused concepts
• Build practical governance artifacts that can also be used in real AI security programmes
• Prepare systematically through domain revision, practice questions and five final mock exams

Table of contents

1. 01How to Use the AAISM Success Toolkit
2. 02Day 0 — AI Literacy Primer
3. 03Domain 1 — AI Governance and Program Management
4. 04AI Governance Concepts and Organizational Readiness
5. 05AI Roles and Responsibilities
6. 06AI Standards, Frameworks and Regulations
7. 07AI Use Cases and the Business Case
8. 08AI Strategy, Policies and Procedures
9. 09Ethical AI, Bias, Fairness and Responsible AI
10. 10AI Asset and Data Governance
11. 11AI Security Program Development
12. 12Domain 1 Rapid Revision
13. 13Domain 2 — AI Risk Management
14. 14AI Trust and Risk Identification
15. 15AI Risk Frameworks and Risk Classification
16. 16Risk Response Strategies and Threat Modelling
17. 17AI Threats, Vulnerabilities and AI-Enabled Attacks
18. 18AI Supply Chain and Third-Party Risk
19. 19Deployer Considerations and Shared Responsibility
20. 20Integration Risk and AI Software Supply Chain
21. 21Domain 2 Rapid Revision
22. 22Domain 3 — AI Technologies and Controls
23. 23Types of AI and Machine Learning
24. 24ML Models and Neural Networks
25. 25Algorithms and AI Vocabulary
26. 26AI Security Architecture and Design
27. 27AI Lifecycle Management
28. 28TEVV, Deployment, Operations and Retirement
29. 29Data Governance and Data Security for AI
30. 30Privacy, Ethics, Trust and Safety
31. 31AI Security Controls and Monitoring
32. 32Awareness Training and Continuous Monitoring
33. 33Domain 3 Rapid Revision
34. 34Final Exam Sprint
35. 35Five Full-Length AAISM Mock Exams
36. 36AAISM Readiness Assessment
37. 37Exam-Day Strategy