Certified MBSE/SysML for AI Security (CSAIS) Certification Program by Tonex
The Certified MBSE/SysML for AI Security (CSAIS) Certification Program by Tonex is designed to equip professionals with the knowledge and expertise to apply Model-Based Systems Engineering (MBSE) and SysML in AI-driven secure system design. This program focuses on enhancing systems engineering processes while addressing the unique challenges posed by AI integration, including complexity, scalability, and lifecycle management.
Participants will learn to apply SysML modeling techniques to improve system traceability, validation, and verification in high-stakes environments. The program emphasizes the importance of building robust and secure AI-enabled architectures that align with regulatory and organizational standards.
From a cybersecurity perspective, CSAIS highlights the role of MBSE and SysML in identifying vulnerabilities early in the design process, enabling secure-by-design frameworks, and reducing risks of cyber threats across interconnected systems. Professionals completing this program will be prepared to lead secure AI-enabled projects with resilience and confidence.
Learning Objectives:
- Understand MBSE principles and SysML applications for AI-driven systems.
- Apply modeling methods to improve system architecture and performance.
- Identify and mitigate AI security vulnerabilities through structured modeling.
- Develop secure system designs aligned with compliance and standards.
- Enhance lifecycle management with AI-enabled MBSE workflows.
- Strengthen system resilience by addressing cybersecurity in MBSE/SysML practices.
Audience:
- Systems Engineers
- AI and Data Engineers
- IT Managers
- Security Architects
- Cybersecurity Professionals
- Project Managers
Program Modules:
Module 1: MBSE Foundations
- MBSE principles and practices
- Role of MBSE in AI systems
- Evolution of system engineering methods
- Integration with AI system lifecycle
- Secure design considerations
- MBSE tool ecosystem
Module 2: SysML Basics
- Core SysML diagram types
- Modeling structure and behavior
- Requirements modeling in SysML
- Traceability in system design
- Visualizing secure system workflows
- SysML best practices
Module 3: AI System Modeling
- Modeling AI system architectures
- Data flow and algorithm integration
- Representing learning components
- AI-specific risks in modeling
- Human-in-the-loop considerations
- Secure data representation
Module 4: Security-Centered MBSE
- Secure-by-design methodologies
- Threat modeling with SysML
- Risk analysis integration
- Attack surface identification
- Compliance-driven security modeling
- Mitigation strategies in MBSE
Module 5: Advanced SysML for AI
- Parametric modeling for AI systems
- System performance and constraints
- AI-specific SysML patterns
- Interoperability modeling
- Multi-domain integration
- Advanced simulation approaches
Module 6: Lifecycle & Implementation
- End-to-end system lifecycle modeling
- Verification and validation in MBSE
- AI deployment considerations
- Continuous assurance processes
- Secure maintenance modeling
- Transitioning from design to operations
Exam Domains:
- MBSE Methodologies and Frameworks
- SysML Modeling Structures and Applications
- AI Integration into Systems Engineering
- Security Threat Analysis in AI Systems
- Compliance and Regulatory Alignment
- Lifecycle Assurance and Risk Management
Course Delivery:
The course is delivered through a combination of lectures, interactive discussions, and project-based learning, facilitated by experts in MBSE, SysML, and AI security. Participants will have access to online resources, including readings, case studies, and tools for practical exercises.
Assessment and Certification:
Participants will be assessed through quizzes, assignments, and a capstone project. Upon successful completion of the course, participants will receive a certificate in Certified MBSE/SysML for AI Security (CSAIS).
Question Types:
- Multiple Choice Questions (MCQs)
- Scenario-based Questions
Passing Criteria:
To pass the Certified MBSE/SysML for AI Security (CSAIS) Certification Training exam, candidates must achieve a score of 70% or higher.
Take the next step in advancing your career by mastering secure AI system design with MBSE and SysML through Tonex’s CSAIS program.