Search Results

Although ISO/SAE 21434 recommends the development of an assurance case for cybersecurity, the precise nature of a cybersecurity case is not explicitly defined within the standard. ...In the case of cybersecurity, this problem is exacerbated by the increasing complexity of vehicular onboard systems, their inherent obscurity due to their heterogenous architecture, emergent behaviors, and the disparate motivations and resources of potential threat agents.

With the rapid development of vehicle intelligent and networking technology, the IT security of automotive systems becomes an important area of research. In addition to the basic vehicle control, intelligent advanced driver assistance systems, infotainment systems will all exchange data with in-vehicle network. Unfortunately, current communication network protocols, including Controller Area Network (CAN), FlexRay, MOST, and LIN have no security services, such as authentication or encryption, etc. Therefore, the vehicle are unprotected against malicious attacks. Since CAN bus is actually the most widely used field bus for in-vehicle communications in current automobiles, the security aspects of CAN bus is focused on. Based on the analysis of the current research status of CAN bus network security, this paper summarizes the CAN bus potential security vulnerabilities and the attack means.

By looking into the vehicle-infrastructure cooperation (VIC) which is oriented towards intelligent, networked and integrated development, this paper analyzes and proposes the essence and development direction of Intelligent Vehicle Infrastructure Cooperation Systems (I-VICS). With an in-depth analysis of technologies of core importance to VIC and influence factors that constrain VIC development as a whole, the paper comes up with a technological route for VIC, and identifies a direction for vehicle-infrastructure cooperative development that progresses from primary to intermediate cooperation, then to advanced cooperation, and finally to full-fledged cooperation. Policy recommendations aiming at strengthening top-level design, building an integrated vehicle-infrastructure-cloud platform, expediting independence of key techs, building robust standards and regulations for VIC, enhancing workforce development as well as greater efforts at market promotion are put forward.

In addition, due to the cyber-security risk, the security functions to ensure the integrity of the message has to be considered.

Automotive safety is always the focus of consumers, the selling point of products, the focus of technology. In order to achieve automatic driving, interconnection with the outside world, human-automatic system interaction, the security connotation of intelligent and connected vehicles (ICV) changes: information security is the basis of its security. Functional safety ensures that the system is operating properly. Behavioral safety guarantees a secure interaction between people and vehicles. Passive security should not be weakened, but should be strengthened based on new constraints. In terms of information safety, the threshold for attacking cloud, pipe, and vehicle information should be raised to ensure that ICV system does not fail due to malicious attacks. The cloud is divided into three cloud platforms according to functions: ICVs private cloud, TSP cloud, public cloud.

This chapter delves into the field of multi-agent collaborative perception (MCP) for autonomous driving: an area that remains unresolved. Current single-agent perception systems suffer from limitations, such as occlusion and sparse sensor observation at a far distance. To address this, three unsettled topics have been identified that demand immediate attention. First, it is crucial to establish normative communication protocols to facilitate seamless information sharing among vehicles. Second, collaboration strategies need to be defined, including identifying the need for specific collaboration projects, determining the collaboration partners, defining the content of collaboration, and establishing the integration mechanism. Finally, collecting sufficient data for MCP model training is vital. This includes capturing diverse modal data and labeling various downstream tasks as accurately as possible.

And as much as there are technical questions regarding network latency, bandwidth, cybersecurity, etc., aspects like human workload, attentiveness, and situational awareness also need to be clarified.

The automotive industry is set for a rapid transformation in the next few years in terms of communication. The kind of growth the automotive industry is poised for in fields of connected cars is both fascinating and alarming at the same time. The communication devices equipped to the cars and the data exchanges done between vehicles to vehicles are prone to a lot of cyber-related attacks. The signals that are sent using Vehicular Adhoc Network (VANET) between vehicles can be eavesdropped by the attackers and it may be used for various attacks such as the man in the middle attack, DOS attack, Sybil attack, etc. These attacks can be prevented using the Blockchain technology, where each transaction is logged in a decentralized immutable Blockchain ledger. This provides authenticity and integrity to the signals. But the use of Blockchain Platforms such as Ethereum has various drawbacks like scalability which makes it infeasible for connected car system.

Also, all the existing methods for vehicular communication rely on a centralized server which itself invite massive cyber-security threats. These threats and challenges can be addressed by using the Blockchain (BC) technology, where each transaction is logged in a decentralized immutable BC ledger.

As vehicles become increasingly connected with the external world, they face a growing range of security vulnerabilities. Researchers, hobbyists, and hackers have compromised security keys used by vehicles' electronic control units (ECUs), modified ECU software, and hacked wireless transmissions from vehicle key fobs and tire monitoring sensors. Malware can infect vehicles through Internet connectivity, onboard diagnostic interfaces, devices tethered wirelessly or physically to the vehicle, malware-infected aftermarket devices or spare parts, and onboard Wi-Fi hotspot. Once vehicles are interconnected, compromised vehicles can also be used to attack the connected transportation system and other vehicles. Securing connected vehicles impose a range of unique new challenges. This paper describes some of these unique challenges and presents an end-to-end cloud-assisted connected vehicle security framework that can address these challenges.

With the rapid development of connected vehicles, the cybersecurity has become an important topic in the automotive network. A spoof ECU can be used to hack the automotive network.

In recent years, with increase in external connectivity (V2X, telematics, mobile projection, BYOD) the automobile is becoming a target of cyberattacks and intrusions. Any such intrusion reduces customer trust in connected cars and negatively impacts brand image (like the recent Jeep Cherokee hack). To protect against intrusion, several mechanisms are available. These range from a simple secure CAN to a specialized symbiote defense software. A few systems (e.g. V2X) implement detection of an intrusion (defined as a misbehaving entity). However, most of the mechanisms require a system-wide change which adds to the cost and negatively impacts the performance. In this paper, we are proposing a practical and scalable approach to intrusion detection. Some benefits of our approach include use of existing security mechanisms such as TrustZone® and watermarking with little or no impact on cost and performance. In addition, our approach is scalable and does not require any system-wide changes.

Autonomous driving represents the ultimate goal of future automobile development. As a collaborative application that integrates vehicles, road infrastructure, network and cloud, autonomous driving business requires a high-degree dynamic cooperation among multiple resources such as data, computing and communications that are distributed throughout the system. In order to meet the anticipated high demand for resources and performance requirements of autonomous driving, and to ensure the safety and comfort of the vehicle users and pedestrians, a top concern of autonomous driving is to understand the system requirements for resources and conduct an in-depth analysis of the autonomous driving business. In this context, this paper presents a comprehensive analysis of the typical business for autonomous driving and establishes an analysis model for five common capabilities, i.e. collection, transmission, intelligent computing, human-machine interaction (HMI), and security.

It is deemed that currently the intelligent connected vehicle (ICV) is in its early stage of development, and it will go through multiple development stages in the future to realize its final goal—autonomous driving. Based on the existing ICV researches, this paper believes that ICV can be used to improve the efficiency and safety of freeway. The current research of ICV has two main directions: one focuses on the traffic flow characteristics of vehicles with different attributes, the other is concerned with using ICV to reduce congestion. From the policies issued by countries around the world and the development plans promoted by major vehicle manufacturers, the future development trends and challenges of ICV are analyzed. ICV must overcome all the shortcomings to achieve its final goal, including insufficient hardware capabilities or excessive cost, and the degree of intelligence that needs to be improved.

Advanced Autonomous Vehicles (AV) for SAE Level 3 and Level 4 functions will lead to a new understanding of the operation phase in the overall product lifecycle. Regulations such as the EU Implementing Act and the German L4 Act (AFGBV) request a continuous field surveillance, the handling of critical E/E faults and software updates during operation. This is required to enhance the Operational Design Domain (ODD) during operation, offering Functions on Demand (FoD), by increasing software features within these autonomous vehicle systems over the entire digital product lifecycle, and to avoid and reduce downtime by a malfunction of the Autonomous Driving (AD) software stack.

Cyber assurance of heavy trucks is a major concern with new designs as well as with supporting legacy systems. Many cyber security experts and analysts are used to working with traditional information technology (IT) networks and are familiar with a set of technologies that may not be directly useful in the commercial vehicle sector. To help connect security researchers to heavy trucks, a remotely accessible testbed has been prototyped for experimentation with security methodologies and techniques to evaluate and improve on existing technologies, as well as developing domain-specific technologies. The testbed relies on embedded Linux-based node controllers that can simulate the sensor inputs to various heavy vehicle electronic control units (ECUs). The node controller also monitors and affects the flow of network information between the ECUs and the vehicle communications backbone.

And as much as there are technical questions regarding network latency, bandwidth, cybersecurity, etc., aspects like human workload, attentiveness, and situational awareness also need to be clarified.

Unmanned ground vehicles (UGVs) may encounter difficulties accommodating environmental uncertainties and system degradations during harsh conditions. However, human experience and onboard intelligence can may help mitigate such cases. Unfortunately, human operators have cognition limits when directly supervising multiple UGVs. Ideally, an automated decision aid can be designed that empowers the human operator to supervise the UGVs. In this paper, we consider a connected UGV platoon under cyber attacks that may disrupt safety and degrade performance. An observer-based resilient control strategy is designed to mitigate the effects of vehicle-to-vehicle (V2V) cyber attacks. In addition, each UGV generates both internal and external evaluations based on the platoons performance metrics. A cloud-based trust-based information management system collects these evaluations to detect abnormal UGV platoon behaviors.

Upon their arrival, Unmanned Autonomous Systems (UAS) brought with them many benefits for those involved in a military campaign. They can use such systems to reconnoiter dangerous areas, provide 24-hr aerial security surveillance for force protection purposes or even attack enemy targets all the while avoiding friendly human losses in the process. Unfortunately, these platforms also carry the inherent risk of being built on innately vulnerable cybernetic systems. From software which can be tampered with to either steal data, damage or even outright steal the aircraft, to the data networks used for communications which can be jammed or even eavesdropped on to gain access to sensible information. All this has the potential to turn the benefits of UAS into liabilities and although the last decade has seen great advances in the development of protection and countermeasures against the described threats and beyond the risk still endures.

Unsettled Issues Regarding Autonomous Vehicles and Open-source Software introduces the impact of software in advanced automotive applications, the role of open-source communities in accelerating innovation, and the important topic of safety and cybersecurity. As electronic functionality is captured in software and a bigger percentage of that software is open-source code, some critical challenges arise concerning security and validation.