Graduate Certificate in Automotive AI Security Techniques
-- ViewingNowThe Graduate Certificate in Automotive AI Security Techniques is a comprehensive course that addresses the growing need for secure AI systems in the automotive industry. This program emphasizes the importance of protecting connected vehicles from cyber-attacks, a critical concern as technology advances.
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Here are the essential units for a Graduate Certificate in Automotive AI Security Techniques:
● Fundamentals of Automotive Cybersecurity: This unit covers the basics of automotive cybersecurity, including common threats, attacks, and defense mechanisms. It also provides an overview of the unique challenges of securing automotive systems.
● AI Security Techniques in Automotive Applications: This unit explores the use of AI and machine learning techniques for securing automotive systems. Topics include intrusion detection, anomaly detection, and threat modeling.
● Secure Architectures for Autonomous Vehicles: This unit focuses on the design and implementation of secure architectures for autonomous vehicles. Topics include secure communication, hardware-based security, and software-defined radio.
● Penetration Testing and Vulnerability Analysis: This unit covers the techniques and tools used for penetration testing and vulnerability analysis of automotive systems. Topics include fuzz testing, reverse engineering, and network traffic analysis.
● Privacy in Automotive Systems: This unit explores the privacy challenges and solutions in automotive systems. Topics include data encryption, access control, and privacy-preserving machine learning.
● Regulations and Standards for Automotive Cybersecurity: This unit covers the regulations and standards related to automotive cybersecurity. Topics include the UN R155 regulation, ISO 21434 standard, and best practices from organizations such as the Auto-ISAC.
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