Security First, Safety Next: The Next-Generation Embedded Sensors for Autonomous Vehicles

The automotive industry is fully shifting towards autonomous connected vehicles. By advancing vehicles’ intelligence and connectivity, the industry has enabled innovative functions such as advanced driver assistance systems (ADAS) in the direction of driverless cars. Such functions are often referred to as cyber-physical features, since almost all of them require collecting data from the physical environment to make automotive operation decisions and properly actuate in the physical world. However, increased functionalities result in increased complexity, which causes serious security vulnerabilities that are typically a result of mushrooming functionality and hence complexity. In a world where we keep seeing traditional mechanical systems shifting to x-by-wire solutions, the number of connected sensors, processing systems, and communication buses inside the car exponentially increases, raising several safety and security concerns. Because there is no safety without security, car manufacturers start struggling in making lightweight sensor and processing systems while keeping the security aspects a major priority. This article surveys the current technological challenges in securing autonomous vehicles and contributes a cross-layer analysis bridging hardware security primitives, real-world side-channel threats, and redundancy-based fault tolerance in automotive electronic control units (ECUs). It combines architectural insights with an evaluation of commercial support for TrustZone, trusted platform modules (TPMs), and lockstep platforms, offering both academic and industry audiences a grounded perspective on gaps in current hardware capabilities. Finally, it outlines future directions and presents a forward-looking vision for securing sensors and processing systems in the path toward fully safe and connected autonomous vehicles.

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Publication Details

Journal
Electronics
Published
2025-05-27
DOI
https://doi.org/10.3390/electronics14112172
Citations
4
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
5.94
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article

Security First, Safety Next: The Next-Generation Embedded Sensors for Autonomous Vehicles

João Sousa, Sandro Pinto, Tiago Gomes, Luís Cunha et al.
4 citations
Electronics
Advanced Malware Detection Techniques
5.94
article

Security First, Safety Next: The Next-Generation Embedded Sensors for Autonomous Vehicles

João Sousa, Sandro Pinto, Tiago Gomes, Luís Cunha, José Azevedo
article en
4 citations

Abstract

The automotive industry is fully shifting towards autonomous connected vehicles. By advancing vehicles’ intelligence and connectivity, the industry has enabled innovative functions such as advanced driver assistance systems (ADAS) in the direction of driverless cars. Such functions are often referred to as cyber-physical features, since almost all of them require collecting data from the physical environment to make automotive operation decisions and properly actuate in the physical world. However, increased functionalities result in increased complexity, which causes serious security vulnerabilities that are typically a result of mushrooming functionality and hence complexity. In a world where we keep seeing traditional mechanical systems shifting to x-by-wire solutions, the number of connected sensors, processing systems, and communication buses inside the car exponentially increases, raising several safety and security concerns. Because there is no safety without security, car manufacturers start struggling in making lightweight sensor and processing systems while keeping the security aspects a major priority. This article surveys the current technological challenges in securing autonomous vehicles and contributes a cross-layer analysis bridging hardware security primitives, real-world side-channel threats, and redundancy-based fault tolerance in automotive electronic control units (ECUs). It combines architectural insights with an evaluation of commercial support for TrustZone, trusted platform modules (TPMs), and lockstep platforms, offering both academic and industry audiences a grounded perspective on gaps in current hardware capabilities. Finally, it outlines future directions and presents a forward-looking vision for securing sensors and processing systems in the path toward fully safe and connected autonomous vehicles.

ElectronicsVol. 14(11)
University of Minho (PT)
Openalex Percentile: Top 4%
Advanced Malware Detection Techniques
5.94
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