Search Results

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.

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.

Reviewer Acknowledgment

Abstract Connected vehicle technology consisting of Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication falls under the umbrella of V2X, or Vehicle-to-Everything, communication. This enables vehicles and infrastructure to exchange safety-related information to enable smarter, safer roads. If driver alerts are raised or automated action is taken as a result of these messages, it is critical that messages are trustworthy and reliable. To this end, the Security Credential Management System (SCMS) and Cooperative Intelligent Transportation Systems (C-ITS) Credential Management System (CCMS) have been proposed to enable authentication and authorization of V2X messages without compromising individual user privacy. This is accomplished by issuing each vehicle a large set of “pseudonyms,” unrelated to any real-world identity. During operation, the vehicle periodically switches pseudonyms, thereby changing its identity to others in the network.

Abstract ICVs are expected to make the transportation safer, cleaner, and more comfortable in the near future. However, the trend of connectivity has greatly increased the attack surfaces of vehicles, which makes in-vehicle networks more vulnerable to cyberattacks which then causes serious security and safety issues. In this article, we therefore systematically analyzed cyberattacks and corresponding countermeasures for in-vehicle networks of intelligent and connected vehicles (ICVs). Firstly, we analyzed the security risk of ICVs and proposed an in-vehicle network model from a hierarchical point of view. Then, we discussed possible cyberattacks at each layer of proposed network model.

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 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 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.

Abstract Modern vehicles integrate Internet of Things (IoT) components to bring value-added services to both drivers and passengers. These components communicate with the external world through different types of interfaces including the on-board diagnostics (OBD-II) port, a mandatory interface in all vehicles in the United States and Europe. While this transformation has driven significant advancements in efficiency and safety, it has also opened a door to a wide variety of cyberattacks, as the architectures of vehicles were never designed with external connectivity in mind, and accordingly, security has never been pivotal in the design. As standardized, the OBD-II port allows not only direct access to the internal network of the vehicle but also installing software on the Electronic Control Units (ECUs).

Abstract In this work, we present an approach to support penetration tests by combining safety and security analyses to enhance automotive security testing. Our approach includes a new way to combine safety and threat analyses to derive possible test cases. We reuse outcomes of a performed safety analysis as the input for a threat analysis. We show systematically how to derive test cases, and we present the applicability of our approach by deriving and performing test cases for a penetration test of an automotive electronic control unit (ECU). Therefore, we selected an airbag control unit due to its safety-critical functionality. During the penetration test, the selected control unit was installed on a test bench, and we were able to successfully exploit a discovered vulnerability, causing the detonation of airbags.

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 importance of in-vehicle network security has increased with an increase in automated and connected vehicles. Hence, many attacks and countermeasures have been proposed to secure the controller area network (CAN), which is an existent in-vehicle network protocol. At the same time, new protocols-such as FlexRay and Ethernet-which are faster and more reliable than CAN have also been proposed. European OEMs have adopted FlexRay as a control network that can perform the fundamental functions of a vehicle. However, there are few studies regarding FlexRay security. In particular, studies on attacks against FlexRay are limited to theoretical studies or simulation-based experiments. Hence, the vulnerability of FlexRay is unclear. Understanding this vulnerability is necessary for the application of countermeasures and improving the security of future vehicles. In this article, we highlight the vulnerability of FlexRay found in the experiments conducted on a real FlexRay network.

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 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 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.

Abstract The rapid development of connected and automated vehicle technologies together with cloud-based mobility services is transforming the transportation industry. As a result, huge amounts of consumer data are being collected and utilized to provide personalized mobility services. Using big data poses serious challenges to data privacy. To that end, the risks of privacy leakage are amplified by data aggregations from multiple sources and exchanging data with third-party service providers, in face of the recent advances in data analytics. This article provides a review of the connected vehicle landscape from case studies, system characteristics, and dataflows. It also identifies potential challenges and countermeasures.