Abstract This paper proposes a reference model for defining security benchmarks for the safety assessment of Cooperative Driving Automation (CDA) applications. Our reference model provides a systematic approach to benchmark the resilience of CDA applications against malicious attacks through extensive system simulations. It enables the test repeatability and comparison of results across different implementations of CDA applications. In our approach, a benchmark is defined as a series of tests that expose the target system to specific attacks while recording its response. Using this model, we define a benchmark for evaluating the resilience of Cooperative Adaptive Cruise Control (CACC) algorithms against barrage jamming attacks targeting the physical layer of the IEEE 802.11p communication standard. We apply this benchmark to assess and compare the performance of four CACC algorithms: P1, Flatbed, Ploeg, and Consensus. The benchmark measures reveal that the Consensus algorithm demonstrates the highest resilience against jamming attacks, primarily due to its heavy reliance on onboard sensors and the use of sensor data from all other vehicles for decision-making. In contrast, the P1 algorithm, which depends mainly on vehicle-to-vehicle (V2V) communication, proves to be the most vulnerable. Furthermore, the results indicate that vehicles are most susceptible to jamming attacks during acceleration phases, making these periods critical for security evaluation. These findings validate the effectiveness of our benchmarking framework in identifying strengths and vulnerabilities of CACC algorithms under cyberattacks.

A remotely operated road vehicle (RORV) refers to a vehicle operated wirelessly from a remote location. In this paper, we report results from an evaluation of two safety mechanisms: safe braking and disconnection. These safety mechanisms are included in the control software for RORV developed by Roboauto, an intelligent mobility solutions provider. The safety mechanisms monitor the communication system to detect packet transmission delays, lost messages, and outages caused by naturally occurring interference as well as denial-of-service (DoS) attacks. When the delay in the communication channel exceeds certain threshold values, the safety mechanisms are to initiate control actions to reduce the vehicle speed or stop the affected vehicle safely as soon as possible. To evaluate the effectiveness of the safety mechanisms, we exposed the vehicle control software to various communication failures using a software-in-the-loop (SIL) testing environment developed specifically for this study. Our results show that the safety mechanisms behaved correctly for a vast majority of the simulated communication failures. However, in a few cases, we noted that the safety mechanisms were triggered incorrectly, either too early or too late, according to the system specification.

This paper presents ComFASE, a communication fault and attack simulation engine. ComFASE is used to identify and evaluate potentially dangerous behaviours of interconnected automated vehicles in the presence of faults and attacks in wireless vehicular networks. ComFASE is built on top of OM-NET++ (a network simulator) and integrates SUMO (a traffic simulator) and Veins (a vehicular network simulator). The tool is flexible in modelling different types of faults and attacks and can be effectively used to study the interplay between safety and cybersecurity attributes by injecting cybersecurity attacks and evaluating their safety implications. To demonstrate the tool, we present results from a series of simulation experiments, where we injected delay and denial-of-service attacks on wireless messages exchanged between vehicles in a platooning application. The results show how different variants of attacks influence the platooning system in terms of collision incidents.

In this work, we evaluate the safety of a platoon of four vehicles under jamming attacks. The platooning application is provided by Plexe-veins, which is a cooperative driving framework, and the vehicles in the platoon are equipped with cooperative adaptive cruise control controllers to represent the vehicles' behavior. The jamming attacks investigated are modeled by extending ComFASE (a Communication Fault and Attack Simulation Engine) and represent three real-world attacks, namely, destructive interference, barrage jamming, and deceptive jamming. The attacks are injected in the physical layer of the IEEE 802.11p communication protocol simulated in Veins (a vehicular network simulator). To evaluate the safety implications of the injected attacks, the experimental results are classified by using the deceleration profiles and collision incidents of the vehicles. The results of our experiments show that jamming attacks on the communication can jeopardize vehicle safety, causing emergency braking and collision incidents. Moreover, we describe the impact of different attack injection parameters (such as, attack start time, attack duration and attack value) on the behavior of the vehicles subjected to the attacks.