Hacking AI-Enhanced Autonomous Vehicles Essentials Training by Tonex
This course explores the vulnerabilities and security challenges of AI-powered autonomous vehicles. Participants gain insights into threat vectors, attack surfaces, and defensive strategies. The training emphasizes real-world attack scenarios, regulatory compliance, and cyber risk management. With the rise of AI in mobility, understanding these risks is critical for future transportation security. Cybersecurity plays a pivotal role in safeguarding autonomous systems from remote exploitation and AI manipulation, ensuring public safety and trust.
Audience:
- Cybersecurity professionals
- Automotive security engineers
- AI system developers
- Embedded system designers
- Compliance officers
- Transportation technology consultants
Learning Objectives:
- Understand AI vulnerabilities in autonomous vehicles
- Identify key attack surfaces in AV architecture
- Explore threat modeling specific to autonomous systems
- Learn mitigation strategies and defensive techniques
- Analyze cybersecurity regulations and compliance needs
Course Modules:
Module 1: Introduction to AI in Autonomous Vehicles
- Role of AI in modern vehicle autonomy
- Key components of AI-AV systems
- Overview of AV software and sensors
- Levels of driving automation
- AI decision-making frameworks
- AV deployment trends and use cases
Module 2: Attack Surfaces in AI-Enhanced Vehicles
- External communications (V2X, V2I) risks
- Vulnerabilities in perception sensors
- Risks in control system algorithms
- Cloud-based service exposure
- Over-the-air update threats
- Access point and interface flaws
Module 3: AI-Specific Threats and Exploits
- Data poisoning in training datasets
- Model inversion and inference attacks
- Adversarial input manipulation
- Spoofing and evasion techniques
- Reinforcement learning attack vectors
- Real-world case studies on AI exploits
Module 4: Defensive Techniques and Mitigation Strategies
- Secure AI model training practices
- Sensor fusion validation methods
- Redundancy and fault tolerance in systems
- Network segmentation and access control
- Incident detection in AV networks
- Threat intelligence for AV cybersecurity
Module 5: Legal, Ethical, and Regulatory Considerations
- Global AV security standards
- NHTSA and ISO 21434 compliance
- Ethical issues in AI-driven mobility
- Cyber liability and responsibility
- Data privacy in autonomous systems
- Governance in connected transportation
Module 6: Future Trends and Security Challenges
- Evolving attack techniques on AVs
- Role of AI in defensive cybersecurity
- Vehicle-to-everything (V2X) security evolution
- Integration of blockchain and AV security
- Threat prediction using AI analytics
- Policy development for emerging AV threats
Protect the future of mobility. Enroll now in Tonex’s Hacking AI-Enhanced Autonomous Vehicles Essentials Training and secure AI-powered transportation.