# A Connected and Autonomous Vehicle Reference Architecture for Attack Surface Analysis
## 2 Related Work
### Reference Architectures
#### 2.1.2 CAV and ITS Reference Architectures  
A functional reference architecture for autonomous driving was introduced in Reference [28], which provided a foundation for considering the functionality of an autonomous vehicle irrespective of its implementation. There are close relations between functional safety and security analysis in the automotive domain. The functional safety analysis relies on information taken from hazard identification, which can be influenced by security aspects such as the communication between the components or access to assets. On the other hand, the implemented countermeasures to address functional safety can determine the security level of the system. As a result, there are certain attempts to integrate security into (functional) safety analysis in CAV, such as SAE J3061 [6]. However, there is insufficient focus on CAV interactions to support using this model for an attack surface analysis. This is because the approach focuses on the vehicle only and does not consider interactions with RSUs, other vehicles, the Internet and other devices. In Reference [7] a security-focused risk assessment was performed for autonomous driving (AD). To achieve this the authors defined a reference architecture by synthesising from multiple academic and industrial AD sources to model select AD applications. The model was instantiated for different selected applications of interest and a risk assessment of the identified threats was performed. The authors note that their work does not attempt to perform an exhaustive specification of threats but to provide ways to specify the system to aid in deriving the threats. The reference architecture and analysis of it performed in our work is similar to this paper, however, we argue that certain details are lacking from this model which prevents a sufficiently in-depth analysis of the attack surface. A reference architecture for ITS infrastructure that focuses on business and organisational aspects of the system was presented in Reference [29]. While the paper does not discuss technical considerations of an ITS system, the organisational aspects highlight certain areas of interaction which are of interest from a security perspective. One issue that was highlighted was that heterogeneous systems had trouble interacting due to different implementations by different suppliers. An adaptor was required to allow these systems to interact, which would be a component of the attack surface. The reference architecture raises the importance of service collaboration, for example, parking and guidance services will need to collaborate to ensure a car is not directed to a full car park. The interactions between these services will also form part of the attack surface. A detailed and comprehensive reference architecture for cooperative and intelligent transport was developed in Reference [8]. There are three components to this architecture, (i) Architecture Reference for Cooperative and Intelligent Transportation (ARC-IT), (ii) Regional Architecture Development for Intelligent Transportation (RAD-IT) and (iii) Systems Engineering Tool for Intelligent Transportation (SET-IT). RAD-IT focuses on tools for regional ITS architectures and SET-IT focuses on assisting with developing \"architectures for pilots, test beds and early deployments\". They key component is ARC-IT when it is used to specify a Functional viewpoint [30] and Communication viewpoint [31]. The architecture is designed to be comprehensive, which is a benefit as the architecture can be used to specify interactions in detail. However, the additional detail adds additional complexity that makes the tool harder to use. There is need for a simpler model that can be easily analysed. The CARMA project [32], which aims to investigate the distribution of the autonomous control functions throughout an ITS defines a three tiered architecture in terms of the CARMA CORE, CARMA EDGE and VEHICLE.