Vehicle Data Protection for Connected Vehicles provides a comprehensive engineering and governance framework for protecting data in modern connected and software-defined vehicles.
As vehicles evolve into complex digital platforms integrating cloud computing, artificial intelligence, mobile applications, and smart city infrastructure, they generate vast amounts of sensitive data. This data including location information, driver behavior, vehicle telemetry, and software updates must be protected against cyber threats, privacy violations, and regulatory non-compliance.
This book introduces the Vehicle Data Protection Framework (VDPF), a structured model designed to help engineers, cybersecurity architects, compliance leaders, and automotive organizations protect vehicle data across the entire connected vehicle ecosystem.
Drawing on modern automotive cybersecurity practices and global regulatory frameworks, the book explains how organizations can design secure vehicle architectures, implement privacy-preserving data platforms, and comply with emerging regulations such as ISO/SAE 21434, UNECE R155, GDPR, the EU Data Act, and the EU AI Act.
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Connected vehicles are rapidly becoming mobile data platforms, generating and exchanging data across complex ecosystems that include cloud services, mobile applications, and urban infrastructure.
Protecting vehicle data is now essential not only for cybersecurity but also for driver privacy, regulatory compliance, and public trust in connected mobility systems.
This book provides the technical architecture, governance models, and security strategies needed to protect vehicle data in the next generation of connected and autonomous vehicles.
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