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Abstract Identity-Anonymized CAN (IA-CAN) protocol is a secure CAN protocol, which provides the sender authentication by inserting a secret sequence of anonymous IDs (A-IDs) shared among the communication nodes. To prevent malicious attacks from the IA-CAN protocol, a secure and robust system error recovery mechanism is required. This article presents a central management method of IA-CAN, named the IA-CAN with a global A-ID, where a gateway plays a central role in the session initiation and system error recovery. Each ECU self-diagnoses the system errors, and (if an error happens) it automatically resynchronizes its A-ID generation by acquiring the recovery information from the gateway. We prototype both a hardware version of an IA-CAN controller and a system for the IA-CAN with a global A-ID using the controller to verify our concept.

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 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 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 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 Secure boot is a fundamental security primitive for establishing trust in computer systems. For real-time safety applications, the time taken to perform the boot measurement conflicts with the need for near instant availability. To speed up the boot measurement while establishing an acceptable degree of trust, we propose a dual-phase secure boot algorithm that balances the strong requirement for data tamper detection with the strong requirement for real-time availability. A probabilistic boot measurement is executed in the first phase to allow the system to be quickly booted. This is followed by a full boot measurement to verify the first-phase results and generate the new sampled space for the next boot cycle. The dual-phase approach allows the system to be operational within a fraction of the time needed for a full boot measurement while producing a high detection probability of data tampering.

Abstract The automotive industry intends to create new services that involve sharing vehicle control information via a wide area network. In modern vehicles, an in-vehicle network shares information between more than 70 electronic control units (ECUs) inside a vehicle while it is driven. However, such a complicated system configuration can result in security vulnerabilities. The possibility of cyber-attacks on vehicles via external services has been demonstrated in many research projects. As advances in vehicle systems (e.g., autonomous drive) progress, the number of vulnerabilities to be exploited by cyber-attacks will also increase. Therefore, future vehicles need security measures to detect unknown cyber-attacks. We propose anomaly-based intrusion detection to detect unknown cyber-attacks for the Control Area Network (CAN) protocol, which is popular as a communication protocol for in-vehicle networks.

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.

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.

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 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 Cyberattacks on financial and government institutions, critical infrastructure, voting systems, businesses, modern vehicles, and so on are on the rise. Fully connected autonomous vehicles are more vulnerable than ever to hacking and data theft. This is due to the fact that the industry still relies on controller area network (CAN) protocol for in-vehicle control networks. The CAN protocol lacks basic security features such as message authentication, which makes it vulnerable to a wide range of attacks including spoofing attacks. This article presents a novel method to protect CAN protocol against packet spoofing, replay, and denial of service (DoS) attacks. The proposed method exploits physical uncolonable attributes in the physical channel between transmitting and destination nodes and uses them for linking the received packet to the source.

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 expansion of the internet has made everyone’s personal and professional lives more transparent. There are network security issues because people like sharing resources under the right conditions. Academics have demonstrated significant interest in situation awareness, which includes situation prediction, situation appraisal, and event detection, rather than focusing on the security of a single device in the network. Multi-stage attack forecasting and security situation awareness are two significant issues for network supervisors because the future usually is unknown. Hence, this study suggests combined intuitionistic fuzzy sets and deep neural network (CIFS-DNN) for network security situation prediction. The goal is to provide network administrators with a resource they can use as a point of reference while they formulate and carry out preventive actions in the event of a network assault.

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 Vehicle-to-Vehicle (V2V) communication is a vehicular communication technology to reduce traffic accidents and congestion. To protect V2V communication, multiple security standards have been developed. This article provides an overview of the China V2V security draft standard and compares it to the American IEEE1609.2 V2V standard and to the Security Credential Management System (SCMS). The article provides an overview of the Chinese cryptographic algorithms used in the China V2V standard, and points out differences in the certificate format, such as the lack of implicit certificates in the China V2V standard. The China V2V PKI architecture is similar to the American SCMS, however, the Chinese system utilizes a set of Root Certificate Authorities (CA) that are trusted via an out-of-band channel whereas the American SCMS supports elector-based addition and revocation of Root CAs.

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 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.

Abstract Aircraft cybersecurity efforts have tended to focus at the strategic or tactical levels without a clear connection between the two. ...CSSEP’s process model postulates that security is best achieved by a balance of cybersecurity, cyber resiliency, defensibility, and recoverability and that control is best established by developing security constraints versus attempting to find every vulnerability. ...CSSEP identifies the major functions needed to do effective aircraft cybersecurity and provides a flexible framework as the “missing link” to connect the strategic and tactical levels of aircraft cybersecurity.

Abstract Threat identification and security analysis have become mandatory steps in the engineering design process of high-assurance systems, where successful cyberattacks can lead to hazardous property damage or loss of lives. This article describes a novel approach to perform security analysis on embedded systems modeled at the architectural level. The tool, called Security Threat Evaluation and Mitigation (STEM), associates threats from the Common Attack Pattern Enumeration and Classification (CAPEC) library with components and connections and suggests potential defense patterns from the National Institute of Standards and Technology (NIST) Special Publication (SP) 800-53 security standard. This article also provides an illustrative example based on a drone package delivery system modeled in AADL.