Secure Data Communication in Autonomous V2X Systems

In Vehicle-to-Everything (V2X) communication systems, vehicles as well as infrastructure devices can interact and exchange data with each other. This capability is used to implement intelligent transportation systems applications. Data confidentiality and integrity need to be preserved in unverified and untrusted environments. In this paper, we propose a solution that provides (a) role-based and attribute-based access control to encrypted data and (b) encrypted search over encrypted data. Vehicle Records contain sensitive information about the owners and vehicles in encrypted form with attached access control policies and policy enforcement engine. Our solution supports decentralized and distributed data exchange, which is essential in V2X systems, where a Central Authority is not required to enforce access control policies. Furthermore, we facilitate querying encrypted Vehicle Records through Structured Query Language (SQL) queries. Vehicle Records are stored in a database in untrusted V2X cloud environment that is prone to provide the attackers with a large attack surface. Big datasets, stored in cloud, can be used for data analysis, such as traffic pattern analysis. Our solution protects sensitive vehicle and owner information from curious or malicious information cloud administrators. Support of indexing improves performance of queries that are forwarded to relevant encrypted Vehicle Records, which are stored in the cloud. We measure the performance overhead of our security solution based on self-protecting Vehicle Records with encrypted search capabilities in V2X communication systems and analyze the effect of security over safety

Prototype to Increase Crosswalk Safety by Integrating Computer Vision with ITS-G5 Technologies

Human errors are probably the main cause of car accidents, and this type of vehicle is one of the most dangerous forms of transport for people. The danger comes from the fact that on public roads there are simultaneously different types of actors (drivers, pedestrians or cyclists) and many objects that change their position over time, making difficult to predict their immediate movements. The intelligent transport system (ITS-G5) standard specifies the European communication technologies and protocols to assist public road users, providing them with relevant information. The scientific community is developing ITS-G5 applications for various purposes, among which is the increasing of pedestrian safety. This paper describes the developed work to implement an ITS-G5 prototype that aims at the increasing of pedestrian and driver safety in the vicinity of a pedestrian crosswalk by sending ITS-G5 decentralized environmental notification messages (DENM) to the vehicles. These messages are analyzed, and if they are relevant, they are presented to the driver through a car’s onboard infotainment system. This alert allows the driver to take safety precautions to prevent accidents. The implemented prototype was tested in a controlled environment pedestrian crosswalk. The results showed the capacity of the prototype for detecting pedestrians, suitable message sending, the reception and processing on a vehicle onboard unit (OBU) module and its presentation on the car onboard infotainment system.info:eu-repo/semantics/publishedVersio

ESIA: An Efficient and Stable Identity Authentication for Internet of Vehicles

Decentralized, tamper-proof blockchain is regarded as a solution to a challenging authentication issue in the Internet of Vehicles (IoVs). However, the consensus time and communication overhead of blockchain increase significantly as the number of vehicles connected to the blockchain. To address this issue, vehicular fog computing has been introduced to improve efficiency. However, existing studies ignore several key factors such as the number of vehicles in the fog computing system, which can impact the consensus communication overhead. Meanwhile, there is no comprehensive study on the stability of vehicular fog composition. The vehicle movement will lead to dynamic changes in fog. If the composition of vehicular fog is unstable, the blockchain formed by this fog computing system will be unstable, which can affect the consensus efficiency. With the above considerations, we propose an efficient and stable identity authentication (ESIA) empowered by hierarchical blockchain and fog computing. By grouping vehicles efficiently, ESIA has low communication complexity and achieves high stability. Moreover, to enhance the consensus security of the hierarchical blockchain, the consensus process is from the bottom layer to the up layer (bottom-up), which we call B2UHChain. Through theoretical analysis and simulation verification, our scheme achieves the design goals of high efficiency and stability while significantly improving the IoV scalability to the power of 1.5 (^1.5) under similar security to a single-layer blockchain. In addition, ESIA has less communication and computation overhead, lower latency, and higher throughput than other baseline authentication schemes

Attacks on self-driving cars and their countermeasures : a survey

Intelligent Traffic Systems (ITS) are currently evolving in the form of a cooperative ITS or connected vehicles. Both forms use the data communications between Vehicle-To-Vehicle (V2V), Vehicle-To-Infrastructure (V2I/I2V) and other on-road entities, and are accelerating the adoption of self-driving cars. The development of cyber-physical systems containing advanced sensors, sub-systems, and smart driving assistance applications over the past decade is equipping unmanned aerial and road vehicles with autonomous decision-making capabilities. The level of autonomy depends upon the make-up and degree of sensor sophistication and the vehicle's operational applications. As a result, self-driving cars are being compromised perceived as a serious threat. Therefore, analyzing the threats and attacks on self-driving cars and ITSs, and their corresponding countermeasures to reduce those threats and attacks are needed. For this reason, some survey papers compiling potential attacks on VANETs, ITSs and self-driving cars, and their detection mechanisms are available in the current literature. However, up to our knowledge, they have not covered the real attacks already happened in self-driving cars. To bridge this research gap, in this paper, we analyze the attacks that already targeted self-driving cars and extensively present potential cyber-Attacks and their impacts on those cars along with their vulnerabilities. For recently reported attacks, we describe the possible mitigation strategies taken by the manufacturers and governments. This survey includes recent works on how a self-driving car can ensure resilient operation even under ongoing cyber-Attack. We also provide further research directions to improve the security issues associated with self-driving cars. © 2013 IEEE

Safety and security co-analysis in transport systems: Current state and regulatory development

Transportation is sensitive to risk. Given the fast development of digitalisation and automation of transport systems in the past decade, new types of security risks (e.g. cyberattacks) emerge within the context of transport safety research. To enable the integrated analysis of emerging security and classical safety-related risks in a holistic manner, safety and security co-analysis (SSCA) is highly demanded for accident prevention. SSCA in transport systems will benefit the risk analysis of complex cyber physical transport systems facing challenges from both hazards and threats. However, the nature of hazard and threat-based risks is fundamentally different, which leads to the various difficulties of analysing them on the same plane. They include the use of different risk parameters, the uncertainty levels of the risk input and the methodologies of risk inference. To address such concerns, this study firstly reviews the literature on SSCA and compares the employed methodologies and their applications within the context of transport systems. Taking into account the advantages of both security-driven and safety-oriented methods, a conceptual framework is proposed to imply the insights on SSCA for transportation through both top-down and bottom-up perspectives, followed by a quantitative illustrative case study. Then, the regulatory development and evolution of SSCA in transport in practice is analysed across different transport modes, which configures initiatives’ interrelations for a cross-fertilisation purpose. As a result, the findings reveal new research directions for the safety of digitalised and/or autonomous transport vehicles and aid in the formation of future transport safety study agendas

Safe and Secure Control of Connected and Automated Vehicles

Evolution of Connected and Automated Vehicles (CAV), as an important class of Cyber-Physical Systems (CPS), plays a crucial role in providing innovative services in transport and traffic management. Vehicle platoons, as a set of CAV, forming a string of connected vehicles, have offered significant enhancements in traffic management, energy consumption, and safety in intelligent transportation systems. However, due to the existence of the cyber layer in these systems, subtle security related issues have been underlined and need to be taken into account with sufficient attention. In fact, despite the benefits brought by the platoons, they potentially suffer from insecure networks which provide the connectivity among the vehicles participating in the platoon which makes these systems prone to be under the risk of cyber attacks. One (or more) external intelligent intruder(s) might attack one (or more) of the vehicles participating in a platoon. In this respect, the need for a safe and secure driving experience is highly sensible and crucial. Hence, we will concentrate on improving the safety and security of CAVs in different scenarios by taking advantage of security related approaches and CAV control systems. In this thesis, we are going to focus on two main levels of platoon control, namely I) High level secure platoon control, and II) Low level secure platoon control. In particular, in the high level part, we consider platoons with arbitrary inter-vehicular communication topoloy whereby the vehicles are able to exchange their driving data with each other through DSRC-based environment. The whole platoon is modeled using graph-theoretic notions by denoting the vehicles as the nodes and the inter-vehicular communication quality as the edge weights. We study the security of the vehicle platoon exposed to cyber attacks using a novel game-theoretic approach. The platoon topologies under investigation are directed (called predecessor following) or undirected (bidirectional) weighted graphs. The attacker-detector game is defined as follows. The attacker targets some vehicles in the platoon to attack and the detector deploys monitoring sensors on the vehicles. The attacker's objective is to be as stealthy to the sensors as possible while the detector tries to place the monitoring sensors to detect the attack impact as much as he can. The existence of equilibrium strategies for this game is investigated based on which the detector can choose specific vehicles to put his sensors on and increase the security level of the system. Moreover, we study the effect of adding (or removing) communication links between vehicles on the game value. We then address the same problem while investigating the optimal actuator placement strategy needed by the defender to mitigate the effects of the attack. In this respect, the energy needed by the attacker to steer the consensus follower-leader dynamics of the system towards his desired direction is used as the game payoff. Simulation and experimental results conducted on a vehicle platoon setup using Robotic Operating System (ROS) demonstrate the effectiveness of our analyses. In the low level platoon control, we exploit novel secure model predictive controller algorithms to provide suitable countermeasure against a prevalent data availability attack, namely Denial-of-Service (DoS) attack. A DoS intruder can endanger the security of platoon by jamming the communication network among the vehicles which is responsible to transmit inter-vehicular data throughout the platoon. In other words, he may cause a failure in the network by jamming it or injecting a huge amount of delay, which in essence makes the outdated transferred data useless. This can potentially result in huge performance degradation or even hazardous collisions. We propose novel secure distributed nonlinear model predictive control algorithms for both static and dynamic nonlinear heterogeneous platoons which are capable of handling DoS attack performed on a platoon equipped by different communication topologies and at the same time they guarantee the desired formation control performance. Notably, in the dynamic case, our proposed method is capable of providing safe and secure control of the platoon in which arbitrary vehicles might perform cut-in and/or cut-out maneuvers. Convergence time analysis of the system are also investigated. Simulation results on a sample heterogeneous attacked platoon exploiting two-predecessor follower communication environment demonstrates the fruitfulness of the method