AI Security for Aerospace & Defense Platforms (AISA-D) Training by Tonex
AI Security for Aerospace & Defense Platforms (AISA-D) Training by Tonex delivers a comprehensive examination of AI-driven systems and their unique security needs in mission-critical environments. This program is designed to address the growing integration of AI agents and foundation models in space, aviation, and defense applications. With national security and operational continuity on the line, the course emphasizes adversarial robustness, secure deployment strategies, and risk mitigation approaches. From algorithmic vulnerabilities to model poisoning threats, participants explore how to safeguard intelligent systems across various domains. The course also highlights the cybersecurity impact of AI integration—focusing on attack surfaces, threat detection, and secure AI lifecycle management.
Audience:
- Cybersecurity Professionals
- Aerospace and Defense Engineers
- AI/ML Developers in Critical Systems
- Security Architects
- Aviation Safety Experts
- Compliance Officers and Risk Analysts
Learning Objectives:
- Understand the role of AI in modern aerospace and defense platforms
- Identify and mitigate AI-specific security risks
- Examine foundation model vulnerabilities and defenses
- Explore adversarial AI techniques and countermeasures
- Learn AI threat modeling approaches for mission-critical environments
- Integrate AI security with existing aerospace and defense cybersecurity policies
Course Modules:
Module 1: AI in Aerospace & Defense
- Overview of AI applications in aviation and space
- Key mission-critical AI use cases
- Integration challenges in defense systems
- Risk landscapes for aerospace AI
- AI deployment lifecycle in A&D
- AI ethics in national defense
Module 2: Threat Landscape for AI Systems
- Unique AI cybersecurity attack surfaces
- Threats to AI integrity and availability
- Data poisoning and backdoor attacks
- Model extraction and evasion threats
- Supply chain security challenges
- Advanced persistent threats using AI
Module 3: Adversarial Robustness Strategies
- Fundamentals of adversarial attacks
- Techniques for improving model robustness
- AI red teaming for A&D use cases
- Defensive training approaches
- Evaluation metrics for robustness
- Challenges in real-time defense
Module 4: Securing Foundation Models
- Architecture of large foundation models
- Fine-tuning vulnerabilities in LLMs
- Prompt injection and misuse scenarios
- Defense mechanisms for large models
- Secure API deployment techniques
- Model access control and auditing
Module 5: Secure AI Lifecycle Management
- Secure model development practices
- Data governance for AI systems
- Secure training environments
- Validation and verification of AI
- Post-deployment monitoring tools
- Patch management and versioning
Module 6: AI Security Governance in A&D
- Regulatory and compliance mandates
- DoD AI security guidelines overview
- NATO and international AI standards
- AI risk management frameworks
- Secure integration with existing systems
- AI audit readiness and documentation
Join Tonex’s AI Security for Aerospace & Defense Platforms (AISA-D) Training to equip yourself with the critical knowledge and strategies needed to secure AI systems in high-stakes environments. Stay ahead of evolving threats and ensure mission assurance through robust, security-first AI deployment practices in aerospace and defense.