Query: Intelligent Connected Vehicles Cyber Security

title: An Overview of Attacks and Defences on Intelligent Connected Vehicles
abstract: Cyber security is one of the most significant challenges in connected vehicular systems and connected vehicles are prone to different cybersecurity attacks that endanger passengers' safety. Cyber security in intelligent connected vehicles is composed of in vehicle security and security of inter vehicle communications. Security of Electronic Control Units (ECUs) and the Control Area Network (CAN) bus are the most significant parts of in vehicle security. Besides, with the development of 4G LTE and 5G remote communication technologies for vehicle toeverything (V2X) communications, the security of inter vehicle communications is another potential problem. After giving a short introduction to the architecture of next generation vehicles including driverless and intelligent vehicles, this review paper identifies a few major security attacks on the intelligent connected vehicles. Based on these attacks, we provide a comprehensive survey of available defences against these attacks and classify them into four categories, i.e. cryptography, network security, software vulnerability detection, and malware detection. We also explore the future directions for preventing attacks on intelligent vehicle systems.

title: Attacks and defences on intelligent connected vehicles: a survey
abstract: Intelligent vehicles are advancing at a fast speed with the improvement of automation and connectivity, which opens up new possibilities for different cyber attacks, including in vehicle attacks (e.g. hijacking attacks) and vehicle to everything communicationattacks (e.g. data theft) These problems are becoming increasingly serious with the development of 4G LTE and 5G communication technologies. Although many efforts are made to improve the resilience to cyber attacks, there are still many unsolved challenges. This paper first identifies some major security attacks on intelligent connected vehicles. Then, we investigate and summarize the available defences against these attacks and classify them into four categories: cryptography, network security, software vulnerability detection, and malware detection. Remaining challenges and future directions for preventing attacks on intelligent vehicle systems have been discussed as well.

title: Cyber Threats Facing Autonomous and Connected Vehicles: Future Challenges
abstract: Vehicles are currently being developed and sold with increasing levels of connectivity and automation. As with all networked computing devices, increased connectivity often results in a heightened risk of a cyber security attack. Furthermore, increased automation exacerbates any risk by increasing the opportunities for the adversary to implement a successful attack. In this paper, a large volume of publicly accessible literature is reviewed and compartmentalized based on the vulnerabilities identified and mitigation techniques developed. This review highlighted that the majority of studies are reactive and vulnerabilities are often discovered by friendly adversaries (white hat hackers) Many gaps in the knowledge base were identified. Priority should be given to address these knowledge gaps to minimize future cyber security risks in the connected and autonomous vehicle sector.

title: Intelligent and Connected Cyber Physical Systems: A Perspective from Connected Autonomous Vehicles
abstract: Cyber physical systems (CPS) have broad applications in the automotive, avionics, robotics, healthcare, and power grid, where the cyber components involving information processing and networking closely interact with the physical processes. Conventionally, there is a separate design flow of CPS. For instance, control algorithms managing the physical dynamics are designed using model based approaches, without considering details of the cyber implementation platforms. Modern CPS are getting increasingly intelligent and connected. A new design methodology taking all the layers of CPS and their interplays into account is being developed, aiming for assurance of safety and security, as well as high robustness and resource efficiency. This chapter presents the technical background of CPS, with an emphasis on the cyber and physical interactions, corresponding to the new design methodology. Case studies on connected autonomous vehicles (CAVs) are used to illustrate the most recent development in CPS.

title: Cloud based Sybil Attack Detection Scheme for Connected Vehicles
abstract: Automated and connected vehicle technologies are among the most heavily researched automotive technologies. As a part of an Intelligent Transportation System (ITS) connected vehicles provide useful information to drivers and the infrastructure to help make safer and more informed decisions. However, vehicle connectivity has made the ITS more vulnerable to security attacks that can endanger vehicle's security as well as driver's safety. Sybil attack is a very common attack, considered dangerous in a distributed network with no centralized authority. When launched against connected vehicles, it consists of controlling a set of vehicles with forged or fake identities to try to alter the measurements and data collected by the ITS, leading to sub optimal decisions. In this paper, we provide a cloud based detection scheme for connected vehicles against such an attack. Contrary to the previous distributed solutions in the literature, this paper presents a cloud based solution that integrates a cloud based authorization unit to authenticate legitimate nodes using symmetric cryptography and real time location tracking. As a centralized authentication system, cloud computing is more reliable and secure in managing the vehicle as a device than any other infrastructure in the vehicular network and can provide real time visibility. A trust evaluation approach is also integrated into the scheme to drive the decisions of the vehicles concerning potential collaborations. The performed experiment and security analysis show the efficacy of our proposed cloud based solution in terms of detection rate, complexity and system requirements.

title: Cyber security in cooperative intelligent transportation systems
abstract: Use of connected vehicles, enabled by the development of information and communication technologies, drastically changed users' experience. Those vehicles are more like a cyber controlled vehicle than a user controlled. With that comprehension and fast growing production of connected vehicles, vehicles are at full exposure to the unwanted malicious attacks. Also, possible implementation scenarios are presented for Cooperative Intelligent Transportation area, where communication between vehicles and infrastructure is essential. Through this research paper, cyber security measurements for lowering chances of unwanted malicious attacks in cooperative intelligent transportation environment are presented.

title: Intelligent Detection of Black Hole Attacks for Secure Communication in Autonomous and Connected Vehicles
abstract: Detection of Black Hole attacks is one of the most challenging and critical routing security issues in vehicular ad hoc networks (VANETs) and autonomous and connected vehicles (ACVs) Malicious vehicles or nodes may exist in the cyber physical path on which the data and control packets have to be routed converting a secure and reliable route into a compromised one. However, instead of passing packets to a neighbouring node, malicious nodes bypass them and drop any data packets that could contain emergency alarms. We introduce an intelligent black hole attack detection scheme (IDBA) tailored to ACV. We consider four key parameters in the design of the scheme, namely, Hop Count, Destination Sequence Number, Packet Delivery Ratio (PDR) and End to End delay (E2E) We tested the performance of our IDBA against AODV with Black Hole (BAODV) Intrusion Detection System (IdsAODV) and EAODV algorithms. Extensive simulation results show that our IDBA outperforms existing approaches in terms of PDR, E2E, Routing Overhead, Packet Loss Rate, and Throughput.

title: Automated Right of Way for Emergency Vehicles in C ITS: An Analysis of Cyber Security Risks
abstract: Cooperative Intelligent Transport Systems (C ITS) provide comprehensive information and communication services to enable a more efficient and safe use of transport systems. Emergency vehicles can benefit from C ITS by sending preemption requests to traffic lights or other connected road users, thus reducing their time loss when approaching an emergency. This, however, depends on a secure and reliable communication between all involved parties. Potential risks involve cyber attacks and acts of sabotage. A major issue is the security process applied to provide C ITS vehicles with the authorisations to exercise the right of way intended for emergency vehicles.

title: Towards a Severity Assessment Method for Potential Cyber Attacks to Connected and Autonomous Vehicles
abstract: CAV (connected and autonomous vehicle) is a crucial part of intelligent transportation systems. CAVs utilize both sensors and communication components to make driving decisions. A large number of companies, research organizations, and governments have researched extensively on the development of CAVs. The increasing number of autonomous and connected functions however means that CAVs are exposed to more cyber security vulnerabilities. Unlike computer cyber security attacks, cyber attacks to CAVs could lead to not only information leakage but also physical damage. According to the UK CAV Cyber Security Principles, preventing CAVs from cyber security attacks need to be considered at the beginning of CAV development. In this paper, a large set of potential cyber attacks are collected and investigated from the aspects of target assets, risks, and consequences. Severity of each type of attacks is then analysed based on clearly defined new set of criteria. The levels of severity for the attacks can be categorized as critical, important, moderate, and minor. Mitigation methods including prevention, reduction, transference, acceptance, and contingency are then suggested. It is found that remote control, fake vision on cameras, hidden objects to LiDAR and Radar, spoofing attack to GNSS, and fake identity in cloud authority are the most dangerous and of the highest vulnerabilities in CAV cyber security.

title: A Generative Policy Model for Connected and Autonomous Vehicles
abstract: Artificial Intelligence is rapidly enhancing human capability by providing support and guidance on a wide variety of tasks. However, one of the main challenges for autonomous systems is effectively managing the decisions and interactions between multiple entities in a dynamic environment. Policies are frequently used in cyber physical systems to define target goals and constraints, such as maximising security whilst preventing communication to unauthorised systems. In this paper we introduce an approach for learning high level policy models for future Connected and Autonomous Vehicles (CAVs) Since CAVs are required to operate in complex, safety critical environments with a wide range of varying contextual conditions, high level policies can help systems achieve their goals whilst adhering to varying environmental constraints. We present a Generative Policy Model (GPM) that enables a CAV to observe, learn, and adapt high level policy models using local knowledge shared by related entities in the environment such as other CAVs, when reliable communication to traditional policy management systems may not be available. Within the proposed CAV GPM architecture, we utilise a novel context free grammar bounded by a set of context sensitive annotations called Answer Set Grammars (ASGs) and perform an evaluation of CAV policy generation in varying contexts. We also release the CAVPolicy dataset of annotated policies to enable future research in this area.