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Abstract Testing and verifying the security of connected and autonomous vehicles (CAVs) under cyber-physical attacks is a critical challenge for ensuring their safety and reliability. Proposed in this article is a novel testing framework based on a model of computation that generates scenarios and attacks in a closed-loop manner, while measuring the safety of the unit under testing (UUT), using a verification vector. The framework was applied for testing the performance of two cooperative adaptive cruise control (CACC) controllers under false data injection (FDI) attacks. Serving as the baseline controller is one of a traditional design, while the proposed controller uses a resilient design that combines a model and learning-based algorithm to detect and mitigate FDI attacks in real-time.

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.

Abstract With the recent advancement in technologies, researchers worldwide have a growing interest in unmanned aerial vehicles (UAVs). The last few years have been significant in terms of its global awareness, adoption, and applications across industries. In UAV-aided wireless networks, there are some limitations in terms of power consumption, data computation, data processing, endurance, and security. So, the idea of UAVs and Edge or Fog computing together deals with the limitations and provides intelligence at the network’s edge, which makes it more valuable to use in emergency applications. Fog computing distributes data in a decentralized way and blockchain also works on the principle of decentralization. Blockchain, as a decentralized database, uses cryptographic methods including hash functions and public key encryption to secure the user information. It is a prominent solution to secure the user’s information in blocks and maintain privacy.

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 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.

Abstract The secure boot has successfully protected systems from executing untrusted software (SW), but low-power controllers lack sufficient time to check every memory cell while satisfying real-time functional safety requirements. Automotive controllers need to maintain security through multiple cycles of remote, unsupervised operation and safely reach a secure state when an anomaly is detected. To accelerate the boot time, we propose Sliced Secure Boot: build fingerprints by slicing orthogonally through memory blocks, protect each cell with a reusable fingerprint using a reproducible pattern with sufficient entropy, and randomly check one fingerprint pattern during boot. We do not claim that sampling offers equivalent protection to exhaustive checks but demonstrate that careful sampling can provide a sufficient level of detection while maintaining compatibility with both startup time and functional safety requirements.

Abstract Vehicular communications face unique security issues in wireless communications. While new vehicles are equipped with a large set of communication technologies, product life cycles are long and software updates are not widespread. The result is a host of outdated and unpatched technologies being used on the street. This has especially severe security impacts because autonomous vehicles are pushing into the market, which will rely, at least partly, on the integrity of the provided information. We provide an overview of the currently deployed communication systems and their security weaknesses and features to collect and compare widely used security mechanisms. In this survey, we focus on technologies that work in an ad hoc manner. This includes Long-Term Evolution mode 4 (LTE-PC5), Wireless Access in Vehicular Environments (WAVE), Intelligent Transportation Systems at 5 Gigahertz (ITS-G5), and Bluetooth.

Abstract Vehicle to Everything (V2X) allows vehicles, pedestrians, and infrastructure to share information for the purpose of preventing accidents, enhancing road safety, and improving the efficiency and energy consumption of transportation. Although V2X messages are authenticated, their content is not validated. Sensor errors or adversarial attacks can cause messages to be perturbed and, therefore, increase the likelihood of traffic jams, compromise the decision process of other vehicles, or provoke fatal crashes. In this article, we introduce V2X Core Anomaly Detection System (VCADS), a system based on the theory presented in [1] and built for the fields provided in the periodic messages shared across vehicles (i.e., Basic Safety Messages, BSMs). VCADS uses physics-based models to constrain the values in each field and detect anomalies by finding the numerical difference between a field and independent derivations of the same field.

Abstract The innovations of vehicle connectivity have been increasing dramatically to enhance the safety and user experience of driving, while the rising numbers of interfaces to the external world also bring security threats to vehicles. Many security countermeasures have been proposed and discussed to protect the systems and services against attacks. To provide an overview of the current states in this research field, we conducted a systematic mapping study (SMS) on the topic area “security countermeasures of in-vehicle communication systems.” A total of 279 papers are identified based on the defined study identification strategy and criteria. We discussed four research questions (RQs) related to the security countermeasures, validation methods, publication patterns, and research trends and gaps based on the extracted and classified data. Finally, we evaluated the validity threats and the whole mapping process.

Automotive cybersecurity issues are becoming more prominent than ever. SAE J3061 and ISO/SAE 21434 being drafted also indicate that automotive cybersecurity has been elevated to a position equal to or more important than functional safety. ...SAE J3061 and ISO/SAE 21434 being drafted also indicate that automotive cybersecurity has been elevated to a position equal to or more important than functional safety. ...Security threat analysis helps the development of the early concept phase of automotive cybersecurity. However, the threat analysis based on the traditional attack tree has the disadvantages of multiple subjective factors and low accuracy.

Abstract Heavy vehicles are essential for the modern economy, delivering critical food, supplies, and freight throughout the world. Connected heavy vehicles are also driven by embedded computers that utilize internal communication using common standards. However, some implementations of the standards leave an opening for a malicious actor to abuse the system. One such abuse case is a cyber-attack known as the “Address Claim Attack.” Proposed in 2018, this attack uses a single network message to disable all communication to and from a target electronic control unit, which may have a detrimental effect on operating the vehicle. This article demonstrates the viability of the attack and then describes the implementation of a solution to prevent this attack in real time without requiring any intervention from the manufacturer of the target devices. The defense technique uses a bit-banged Controller Area Network (CAN) filter to detect the attack.

Abstract In the automotive domain, the evolution of electrical and electronic (E/E) architecture trend is toward consolidating multiple heterogeneous applications executing on individual devices onto a centralized powerful computing platform. Many forums debate the nature of this centralized computing platform. At least for another decade, automotive powertrain functions will continue their development on a multicore controller platform (MCU) instead of many core processors. Data security and the need to meet Automotive Safety Integrity Level D (ASIL-D)-compliant powertrain functions are some of the reasons for this preference. For the centralized computing platform, virtualizing the underlying MCU will facilitate the simultaneous execution of heterogeneous powertrain applications with guaranteed spatial and temporal isolation. A common problem in virtualizing the MCU is the sharing of peripherals, which are comparatively scarce.

Ensuring cybersecurity in an ECU network is challenging as there is no centralized authority in the vehicle to provide security as a service. ...While progress has been made to address cybersecurity vulnerabilities, many of these approaches have focused on enterprise, software-centric systems and require more computational resources than typically available for onboard vehicular devices.

Abstract Connected vehicles and intelligent transportation systems are currently evolving into highly interconnected digital environments. Due to the interconnectivity of different systems and complex communication flows, a joint risk analysis for combining safety and security from a system perspective does not yet exist. We introduce a novel method for joint risk assessment in the automotive sector as a combination of the Diamond Model, Failure Mode and Effects Analysis (FMEA), and Factor Analysis of Information Risk (FAIR). These methods have been sequentially composed, which results in a comprehensive risk management approach to information security in an intelligent transport system (ITS). The Diamond Model serves to identify and structurally describe threats and scenarios, the widely accepted FMEA provides threat analysis by identifying possible error combinations, and FAIR provides a quantitative estimation of probabilities for the frequency and magnitude of risk events.

Abstract Despite more and more rigorous defense mechanisms in place for cyber-physical systems, cybercriminals are increasingly attacking systems for benefits using a variety of means including malware, phishing, ransomware, and denial of service. Cyberattacks could not only cause significant economic loss but also disastrous consequences for individuals and organizations. Therefore, it is advantageous to detect and fix potential cyber vulnerabilities before the system is fielded. To this end, this article presents a language, VERDICT, and a novel framework, Cyber Vulnerability Analysis Framework (CyVAF) to (i) define cyber threats and mitigation defenses based on system properties, (ii) detect cyber vulnerabilities of system architecture automatically, and also (iii) suggest mitigation defenses. VERDICT is developed as an annex to the Architecture Analysis and Design Language (AADL) but can also be used independently.

Abstract Automotive cybersecurity engineers now have the challenge of delivering Risk Assessments of their products using a method that is described in the new standard for automotive cybersecurity: International Organization for Standardization/Society of Automotive Engineers (ISO/SAE) 21434. ...Abstract Automotive cybersecurity engineers now have the challenge of delivering Risk Assessments of their products using a method that is described in the new standard for automotive cybersecurity: International Organization for Standardization/Society of Automotive Engineers (ISO/SAE) 21434.

Reviewer Acknowledgment

Abstract Connecting vehicles to various network services increases the risk of in-vehicle cyberattacks. For automotive industries, the supply chain for assembling a vehicle consists of many different organizations such as component suppliers, system suppliers, and car manufacturers (CMs). Moreover, once a vehicle has shipped from the factory of the CM, resellers, dealers, and owners of the vehicle may add and replace the optional authorized and third-party equipment. Such equipment may have serious security vulnerabilities that may be targeted by a malicious attacker. The key management system of a vehicle must be applicable to all use cases. We propose a novel key management system adaptable to the electronic control unit (ECU) lifecycle of a vehicle. The scope of our system is not only the vehicle product line but also the third-party vendors of automotive accessories and vehicle maintenance facilities, including resellers, dealers, and vehicle users.

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 This work introduces the concept of a dual-layer specification structure for standards that separate interoperability functions, such as backward compatibility, localization, and deployment, from those essential to reliability, security, and functionality. The latter group of features, which constitute the actual standard, make up the baseline layer for instructions, while all the elements required for interoperability are specified in a second layer, known as a Protocols, Operations, Usage, and Formats (POUF) document. We applied this technique in the development of a standard for Uptane [1], a security framework for over-the-air (OTA) software updates used in many automobiles. This standard is a good candidate for a dual-layer specification because it requires communication between entities, but does not require a specific format for this communication.