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Abstract In the automotive domain, the overall complexity of technical components has increased enormously. Formerly isolated, purely mechanical cars are now a multitude of cyber-physical systems that are continuously interacting with other IT systems, for example, with the smartphone of their driver or the backend servers of the car manufacturer. This has huge security implications as demonstrated by several recent research papers that document attacks endangering the safety of the car. However, there is, to the best of our knowledge, no holistic overview or structured description of the complex automotive domain. Without such a big picture, distinct security research remains isolated and is lacking interconnections between the different subsystems. Hence, it is difficult to draw conclusions about the overall security of a car or to identify aspects that have not been sufficiently covered by security analyses.

Abstract In the pursuit of advancing autonomous vehicles (AVs), data-driven algorithms have become pivotal in replacing human perception and decision-making. While deep neural networks (DNNs) hold promise for perception tasks, the potential for catastrophic consequences due to algorithmic flaws is concerning. A well-known incident in 2016, involving a Tesla autopilot misidentifying a white truck as a cloud, underscores the risks and security vulnerabilities. In this article, we present a novel threat model and risk assessment (TARA) analysis on AV data storage, delving into potential threats and damage scenarios. Specifically, we focus on DNN parameter manipulation attacks, evaluating their impact on three distinct algorithms for traffic sign classification and lane assist.

Abstract Automotive software is increasingly complex and critical to safe vehicle operation, and related embedded systems must remain up to date to ensure long-term system performance. Update mechanisms and data modification tools introduce opportunities for malicious actors to compromise these cyber-physical systems, and for trusted actors to mistakenly install incompatible software versions. A distributed and stratified “black box” audit trail for automotive software and data provenance is proposed to assure users, service providers, and original equipment manufacturers (OEMs) of vehicular software integrity and reliability. The proposed black box architecture is both layered and diffuse, employing distributed hash tables (DHT), a parity system and a public blockchain to provide high resilience, assurance, scalability, and efficiency for automotive and other high-assurance systems.

Abstract The United Nation Economic Commission for Europe (UNECE) Regulation 155—Cybersecurity and Cybersecurity Management System (UN R155) mandates the development of cybersecurity management systems (CSMS) as part of a vehicle’s lifecycle. ...Due to the focus of R155 and its suggested implementation guideline, ISO/SAE 21434:2021—Road Vehicle Cybersecurity Engineering, mainly centering on the alignment of cybersecurity risk management to the vehicle development lifecycle, there is a gap in knowledge of proscribed activities for validation and verification testing. ...An inherent component of the CSMS is cybersecurity risk management and assessment. Validation and verification testing is a key activity for measuring the effectiveness of risk management, and it is mandated by UN R155 for type approval.

As a promising strategic industry group that is rapidly evolving around the world, autonomous vehicle is entering a critical phase of commercialization from demonstration to end markets. The global automotive industry and governments are facing new common topics and challenges brought by autonomous vehicle, such as how to test, assess, and administrate the autonomous vehicle to ensure their safe running in real traffic situations and proper interactions with other road users. Starting from the facts that the way to autonomous driving is the process of a robot or a machine taking over driving tasks from a human. This paper summarizes the main characteristics of autonomous vehicle which are different from traditional one, then demonstrates the limitations of the existing certification mechanism and related testing methods when applied to autonomous vehicle.

Abstract Connected autonomous vehicles that employ internet connectivity are technologically complex, which makes them vulnerable to cyberattacks. Many cybersecurity researchers, white hat hackers, and black hat hackers have discovered numerous exploitable vulnerabilities in connected vehicles. ...This study expanded the technology acceptance model (TAM) to include cybersecurity and level of trust as determinants of technology acceptance. This study surveyed a diverse sample of 209 licensed US drivers over 18 years old.

As technology and functionality of vehicle systems change, so do data recording needs. In ADS-dedicated vehicles (DV), the ADS perceives the environment and handles vehicle motion control, i.e., the dynamic driving task (DDT), as described in SAE J3016. When an ADS takes the place of a human driver, its sensing, processing, and control systems necessitate new considerations for data recording. Data recording is important to crash reconstruction, system performance investigations, and event analysis. It enables industry-wide improvements in ADS safety. This best practice makes recommendations for the ADS-DV data needed to support: (1) information about what the ADS "saw" and "did" and (2) identify the technology-relevant factors that contributed to the event.

An ADS-operated vehicle’s operational design domain (ODD) is defined by the manufacturer based on numerous factors. Research is underway at other organizations to define and organize ODD elements into taxonomies and other relational constructs. In order to enhance collaboration and communication between manufacturers and developers and transportation authorities, common terms and consistent frameworks are needed. The conceptual framework presented by Automated Vehicle Safety Consortium establishes a lexicon that can be used consistently by ADS developers and manufacturers responsible for defining their ADS ODD. A common framework and lexicon will reduce confusion, align expectations, and therefore build public trust, acceptance, and confidence.

AVSC Best Practice for Interactions Between ADS-DVs and Vulnerable Road Users (VRUs) AVSC00009202208 establishes common terminology and a baseline understanding of the challenges posed, and framework to evaluate automated driving system-dedicated vehicle (ADS-DV) interactions with VRUs. This best practice can facilitate communication among the industry and public, help calibrate expectations of all traffic participants, and improve broader acceptance of SAE level 4 and level 5 ADS-equipped vehicles.

AVSC Information Report for Change Risk Management AVSC00010202304 provides a process for change risk management for fleet-operated ADS-DVs using level 4 or 5 automation. The document addresses risks resulting from planned and unplanned changes in an ADS-DV design and/or operation. This information report is based on the concept of risk-informed decision-making. Making risk management decisions such as safety and change management, safety analysis, and safety assurance are especially applicable when moving from concept to production intent for the ADS-DV. Change Risk Management (CRM) does not replace best practices or other methods for managing safety anomalies or change management processes. It may instead be viewed as an additional resource that elaborates on how safety anomaly management and change management can be performed.

Access control enforces security policies for controlling critical resources. For V2X (Vehicle to Everything) autonomous military vehicle fleets, network middleware systems such as ROS (Robotic Operating System) expose system resources through networked publisher/subscriber and client/server paradigms. Without proper access control, these systems are vulnerable to attacks from compromised network nodes, which may perform data poisoning attacks, flood packets on a network, or attempt to gain lateral control of other resources. Access control for robotic middleware systems has been investigated in both ROS1 and ROS2. Still, these implementations do not have mechanisms for evaluating a policy's consistency and completeness or writing expressive policies for distributed fleets. We explore an RBAC (Role-Based Access Control) mechanism layered onto ROS environments that uses local permission caches with precomputed truth tables for fast policy evaluation.

The separation of cybersecurity considerations in RMTO is barely considered, as so far, most available research and activities are mainly focused on AV. ...The main focus of this paper is addressing RMTO cybersecurity utilising an adaptable security-by-design approach, although security-by-design is still in the infant state within automotive cybersecurity. ...The main focus of this paper is addressing RMTO cybersecurity utilising an adaptable security-by-design approach, although security-by-design is still in the infant state within automotive cybersecurity. An adaptable security-by-design approach for RMTO covers Security Engineering Life-cycle, Logical Security Layered Concept, and Security Architecture.

This increases the attractiveness of an attack on vehicles and thus introduces new risks for vehicle cybersecurity. Thus, just as safety became a critical part of the development in the late 20th century, the automotive domain must now consider cybersecurity as an integral part of the development of modern vehicles. ...Thus, just as safety became a critical part of the development in the late 20th century, the automotive domain must now consider cybersecurity as an integral part of the development of modern vehicles. Aware of this fact, the automotive industry has, therefore, recently taken multiple efforts in designing and producing safe and secure connected and automated vehicles. ...As the domain geared up for the cybersecurity challenges, they leveraged experiences from many other domains, but must face several unique challenges.

Argus, a global leader in automotive cybersecurity, has upgraded its stand-alone Fleet Protection backend platform and is now providing continuous live monitoring of both automotive and commercial aircraft fleets.

Abstract Over the past forty years, the Electronic Control Unit (ECU) technology has grown in both sophistication and volume in the automotive sector, and modern vehicles may comprise hundreds of ECUs. ECUs typically communicate via a bus-based network architecture to collectively support a broad range of safety-critical capabilities, such as obstacle avoidance, lane management, and adaptive cruise control. However, this technology evolution has also brought about risks: if ECU firmware is compromised, then vehicle safety may be compromised. Recent experiments and demonstrations have shown that ECU firmware is not only poorly protected but also that compromised firmware may pose safety risks to occupants and bystanders.

Ransomware is not a new method of malware infection. This historically had been experienced in the enterprise in nearly every industry. This has been especially problematic in the medical and manufacturing fields. As the attackers saturate the specifically targeted industries, the attackers will expand their target industries. One of these which has not been significantly explored by the ransomware groups are the embedded systems and automobile environment. This set of targets is massive and provides for a vast attack potential. While this has not experienced this attack methodology at length, the research and efforts are creeping towards this as a natural extension of the business. The research focusses on the history of ransomware, uses in the enterprise, possible attack vectors with ground vehicles, and defenses to be explored and implemented to secure automobiles, fleets, and the industries.

SAE International and General Motors have partnered to headline sponsor AutoDrive Challenge™, the latest of SAE International’s Collegiate Design Series.

To better inform and equip mobility engineers dealing with these challenges, SAE International has released a new book series from Juan R. Pimentel that explores automated vehicle safety concepts and technologies.

IOOs and ADS developers agree that cost, communications, interoperability, cybersecurity, operation, maintenance, and other issues undercut efforts to deploy a comprehensive connected infrastructure.

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