ISO 27090 — Cybersecurity AI Security — Certification Brochure

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London Academy of Professional Training
Certificate
ISO 27090 — Cybersecurity AI Security
ISO Certification Programme
REF: IIT-AII-27090  •  ISO IT & Related Technologies  •  Artificial Intelligence
6Subjects 25Chapters 144Classes 430Total Marks 60%Pass Mark LifetimeValidity
At a Glance
ReferenceIIT-AII-27090
AwardCertificate
Assessment430 marks — 258 to pass (60%)
PrerequisitesNone
ValidityLifetime
Awarding BodyLAPT — London Academy of Professional Training
Curriculum
1 AI Threat Assessment and Risk Management 5 chapters · 30 classes  85 marks
• 1 Understanding AI Threat Landscape — 6 classes
› 1.1 Identify Key AI Threats in Cybersecurity
› 1.2 Analyze the Impact of AI Vulnerabilities on Systems
› 1.3 Evaluate Real-World Case Studies of AI Threats
› 1.4 Assess Risk Levels Associated with AI Technologies
› 1.5 Develop Strategies for Mitigating AI-Related Risks
› 1.6 Create an AI Threat Assessment Framework for Organizations
• 2 Identifying AI-Specific Risks — 6 classes
› 2.1 Analyze the Unique Risks Associated with AI Technologies
› 2.2 Evaluate Case Studies of AI Security Breaches
› 2.3 Identify Vulnerabilities in AI Systems and Algorithms
› 2.4 Assess the Impact of AI on Organizational Risk Profiles
› 2.5 Develop Strategies to Mitigate AI-Specific Risks
› 2.6 Create an AI Risk Assessment Framework for Implementation
• 3 Risk Assessment Frameworks for AI Systems — 6 classes
› 3.1 Identify Key Components of Risk Assessment Frameworks for AI
› 3.2 Analyze Different Risk Assessment Models Applied to AI Systems
› 3.3 Evaluate Vulnerabilities Specific to AI Technologies
› 3.4 Develop Risk Scenarios Relevant to AI Implementation
› 3.5 Prioritize Risks Using a Risk Matrix for AI Systems
› 3.6 Formulate Mitigation Strategies for Identified AI Risks
• 4 Mitigation Strategies for AI Threats — 6 classes
› 4.1 Identify Common AI Threats in Cybersecurity
› 4.2 Analyze Vulnerabilities of AI Systems
› 4.3 Develop Risk Assessment Frameworks for AI
› 4.4 Implement Mitigation Techniques for Identified Risks
› 4.5 Monitor AI Systems for Emerging Threats
› 4.6 Evaluate the Effectiveness of Mitigation Strategies
• 5 Implementing an AI Risk Management Program — 6 classes
› 5.1 Identify Key Components of an AI Risk Management Program
› 5.2 Conduct a Threat Assessment for AI Systems
› 5.3 Develop Risk Assessment Methodologies for AI Applications
› 5.4 Establish Metrics for Evaluating AI Risks
› 5.5 Create an Action Plan for Mitigating AI Risks
› 5.6 Communicate AI Risk Management Strategies to Stakeholders
2 Data Privacy and Compliance in AI Systems 5 chapters · 30 classes  45 marks
• 1 Understanding Data Privacy Principles in AI Systems — 6 classes
› 1.1 Define Key Data Privacy Principles in AI Systems
› 1.2 Explore the Importance of Consent in Data Handling
› 1.3 Analyze Data Minimization Strategies for AI Applications
› 1.4 Examine User Rights and AI: Access, Deletion, and Corrections
› 1.5 Assess Compliance Risks and Accountability in AI Systems
› 1.6 Implement Best Practices for Data Privacy in AI Development
• 2 Regulatory Frameworks Impacting AI Data Practices — 6 classes
› 2.1 Analyze Key Regulatory Frameworks Impacting AI Data Practices
› 2.2 Identify Data Privacy Principles Under GDPR for AI Systems
› 2.3 Examine Compliance Requirements for AI in Data Protection Legislation
› 2.4 Evaluate the Role of National Data Protection Authorities in AI Governance
› 2.5 Assess the Impact of Global Regulatory Trends on AI Deployment
› 2.6 Develop a Compliance Checklist for AI Data Privacy Practices
• 3 Risk Assessment and Management for AI Data Compliance — 6 classes
› 3.1 Identify Key Risks in AI Data Processing
› 3.2 Evaluate Compliance Requirements for AI Systems
› 3.3 Develop a Risk Assessment Framework for AI
› 3.4 Analyze Common Vulnerabilities in AI Data Security
› 3.5 Implement Mitigation Strategies for Identified Risks
› 3.6 Review and Update Risk Management Practices Regularly
• 4 Implementing Data Protection by Design in AI Development — 6 classes
› 4.1 Identify Key Principles of Data Protection by Design in AI
› 4.2 Analyze Regulatory Requirements for AI Data Protection
› 4.3 Evaluate Existing AI Systems for Data Privacy Compliance
› 4.4 Design an Implementation Plan for Data Protection in AI Projects
› 4.5 Develop Risk Assessment Strategies for AI Data Privacy
› 4.6 Create a Data Protection Audit Checklist for AI Applications
• 5 Monitoring and Auditing AI Systems for Data Privacy Compliance — 6 classes
› 5.1 Identify Key Regulations Impacting AI Data Privacy
› 5.2 Understand the Role of Monitoring in Compliance Frameworks
› 5.3 Develop a Data Privacy Audit Checklist for AI Systems
› 5.4 Implement Continuous Monitoring Techniques for AI Compliance
› 5.5 Analyze Case Studies of AI Compliance Failures
› 5.6 Create a Compliance Reporting Strategy for AI Systems
3 Evaluating Cybersecurity Strategies Effectiveness 0 chapters  65 marks
4 Implementing ISO 27090 Standards 5 chapters · 30 classes  105 marks
• 1 Understanding ISO 27090: Overview and Importance in Cybersecurity AI — 6 classes
› 1.1 Define ISO 27090 and its Role in Cybersecurity AI
› 1.2 Identify Key Components and Principles of ISO 27090
› 1.3 Analyze the Importance of ISO 27090 for AI Security
› 1.4 Explore Case Studies: ISO 27090 Implementation in Organizations
› 1.5 Evaluate the Benefits and Challenges of Adopting ISO 27090
› 1.6 Develop a Strategy for Implementing ISO 27090 Standards in Your Organization
• 2 Key Principles and Frameworks of ISO 27090 Implementation — 6 classes
› 2.1 Understand Key Principles of ISO 27090 Standards
› 2.2 Explore the Framework for ISO 27090 Implementation
› 2.3 Identify Stakeholders in ISO 27090 Compliance
› 2.4 Assess Current Cybersecurity Posture Against ISO 27090
› 2.5 Develop an Action Plan for ISO 27090 Adoption
› 2.6 Evaluate the Effectiveness of ISO 27090 Implementation
• 3 Risk Assessment and Management in Cybersecurity AI Under ISO 27090 — 6 classes
› 3.1 Identify Key Risks in Cybersecurity AI Systems
› 3.2 Analyze Vulnerabilities in AI Implementation
› 3.3 Evaluate Threats Specific to Cybersecurity AI
› 3.4 Develop a Risk Assessment Framework for AI
› 3.5 Mitigate Risks Through Effective Management Strategies
› 3.6 Implement Continuous Monitoring for AI Risk Management
• 4 Developing Policies and Procedures for ISO 27090 Compliance — 6 classes
› 4.1 Identify Core Components of ISO 27090 Policies
› 4.2 Develop Risk Assessment Procedures for Compliance
› 4.3 Establish Data Protection Guidelines under ISO 27090
› 4.4 Create Incident Response Policies for AI Security
› 4.5 Integrate Training and Awareness Programs for ISO Compliance
› 4.6 Evaluate and Revise Policies for Continuous Improvement
• 5 Assessing and Maintaining ISO 27090 Compliance in Cybersecurity AI — 6 classes
› 5.1 Evaluate Current Cybersecurity AI Practices Against ISO 27090 Standards
› 5.2 Identify Gaps in Compliance and Risk Management Strategies
› 5.3 Develop a Compliance Assessment Framework for Cybersecurity AI
› 5.4 Implement Continuous Monitoring Techniques for ISO 27090 Compliance
› 5.5 Conduct Regular Audits to Ensure Ongoing ISO 27090 Compliance
› 5.6 Create an Action Plan for Addressing Non-Compliance Issues in Cybersecurity AI
5 Incident Response Planning for AI 5 chapters · 30 classes  65 marks
• 1 Understanding Incident Response in AI Contexts — 6 classes
› 1.1 Define Incident Response in AI Contexts
› 1.2 Identify Key Components of an AI Incident Response Plan
› 1.3 Assess Risks and Threats Unique to AI Systems
› 1.4 Develop Response Strategies for AI Incidents
› 1.5 Implement Communication Protocols During an AI Incident
› 1.6 Evaluate and Improve Incident Response Plans for AI
• 2 Frameworks and Standards for AI Incident Response Planning — 6 classes
› 2.1 Analyze Existing AI Incident Response Frameworks
› 2.2 Identify Key Standards for AI Security Compliance
› 2.3 Evaluate the Role of Stakeholders in Incident Response
› 2.4 Develop a Tailored Incident Response Plan for AI
› 2.5 Practice Incident Response Scenarios in AI Contexts
› 2.6 Assess and Improve Incident Response Plans Post-Incident
• 3 Risk Assessment and Threat Modeling for AI Systems — 6 classes
› 3.1 Identify Key AI Risks in Incident Response
› 3.2 Analyze Threat Vectors Specific to AI Systems
› 3.3 Evaluate Vulnerabilities in AI Model Architectures
› 3.4 Assess Impact and Likelihood of AI Threats
› 3.5 Create a Risk Mitigation Strategy for AI Incidents
› 3.6 Implement Continuous Monitoring for AI Threats
• 4 Developing AI-Specific Incident Response Procedures — 6 classes
› 4.1 Understand the Unique Challenges of AI in Incident Response
› 4.2 Identify Key Stakeholders for AI Incident Management
› 4.3 Develop AI-Specific Incident Detection Techniques
› 4.4 Create AI Incident Response Team Roles and Responsibilities
› 4.5 Design an AI Incident Response Playbook
› 4.6 Conduct a Tabletop Exercise for AI Incident Scenarios
• 5 Testing, Training, and Continuous Improvement for AI Incident Responses — 6 classes
› 5.1 Assess Current AI Incident Response Models
› 5.2 Develop Simulation Scenarios for AI Incidents
› 5.3 Conduct Tabletop Exercises for Team Preparedness
› 5.4 Analyze Response Outcomes and Identify Gaps
› 5.5 Implement Continuous Training Programs for Staff
› 5.6 Review and Revise Incident Response Plans Regularly
6 Security Awareness and Culture Development 5 chapters · 24 classes  65 marks
• 1 Understanding the Importance of Security Awareness in Cybersecurity — 6 classes
› 1.1 Identify Key Components of Security Awareness
› 1.2 Assess the Current Security Culture in Your Organization
› 1.3 Explore Common Cyber Threats and Their Impact
› 1.4 Develop Strategies to Enhance Security Awareness
› 1.5 Create Engaging Security Training Programs for Employees
› 1.6 Evaluate the Effectiveness of Security Awareness Initiatives
• 2 Identifying Common Cybersecurity Threats and Vulnerabilities — 6 classes
› 2.1 Define Cybersecurity Threats and Vulnerabilities
› 2.2 Identify Major Types of Cybersecurity Threats
› 2.3 Analyze Common Vulnerabilities in Digital Systems
› 2.4 Explore Real-World Examples of Cybersecurity Breaches
› 2.5 Assess Organizational Risk Factors Related to Cyber Threats
› 2.6 Develop Strategies for Mitigating Cybersecurity Risks
• 3 Building a Cybersecurity Awareness Program — 6 classes
› 3.1 Identify Key Components of a Cybersecurity Awareness Program
› 3.2 Assess Current Organizational Security Culture
› 3.3 Develop Engaging Training Materials for Cybersecurity Awareness
› 3.4 Implement Effective Communication Strategies for Program Launch
› 3.5 Measure the Impact of Cybersecurity Awareness Initiatives
› 3.6 Foster Continuous Improvement in Cybersecurity Culture
• 4 Engaging Employees in Cybersecurity Practices — 6 classes
› 4.1 Foster a Cybersecurity Culture in the Workplace
› 4.2 Identify Common Cyber Threats and Vulnerabilities
› 4.3 Recognize Security Best Practices for Daily Operations
› 4.4 Encourage Open Communication About Cybersecurity Concerns
› 4.5 Develop Engaging Training Programs for Staff
› 4.6 Implement Feedback Mechanisms to Improve Cyber Awareness
• 5 Evaluating and Sustaining Security Awareness Initiatives
LAPT — 85 Great Portland Street, W1W 7LT, London, United Kingdom
info@lapt.org  •  +44 7513 283044  •  lapt.org		 UKPRN 10067351  •  Company 4984798
Curriculum current at the date of issue.