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As a promising strategic industry group that is rapidly evolving around the world, autonomous vehicle is entering a critical phase of commercialization from demonstration to end markets. The global automotive industry and governments are facing new common topics and challenges brought by autonomous vehicle, such as how to test, assess, and administrate the autonomous vehicle to ensure their safe running in real traffic situations and proper interactions with other road users. Starting from the facts that the way to autonomous driving is the process of a robot or a machine taking over driving tasks from a human. This paper summarizes the main characteristics of autonomous vehicle which are different from traditional one, then demonstrates the limitations of the existing certification mechanism and related testing methods when applied to autonomous vehicle.

Access control enforces security policies for controlling critical resources. For V2X (Vehicle to Everything) autonomous military vehicle fleets, network middleware systems such as ROS (Robotic Operating System) expose system resources through networked publisher/subscriber and client/server paradigms. Without proper access control, these systems are vulnerable to attacks from compromised network nodes, which may perform data poisoning attacks, flood packets on a network, or attempt to gain lateral control of other resources. Access control for robotic middleware systems has been investigated in both ROS1 and ROS2. Still, these implementations do not have mechanisms for evaluating a policy's consistency and completeness or writing expressive policies for distributed fleets. We explore an RBAC (Role-Based Access Control) mechanism layered onto ROS environments that uses local permission caches with precomputed truth tables for fast policy evaluation.

The separation of cybersecurity considerations in RMTO is barely considered, as so far, most available research and activities are mainly focused on AV. ...The main focus of this paper is addressing RMTO cybersecurity utilising an adaptable security-by-design approach, although security-by-design is still in the infant state within automotive cybersecurity. ...The main focus of this paper is addressing RMTO cybersecurity utilising an adaptable security-by-design approach, although security-by-design is still in the infant state within automotive cybersecurity. An adaptable security-by-design approach for RMTO covers Security Engineering Life-cycle, Logical Security Layered Concept, and Security Architecture.

Ransomware is not a new method of malware infection. This historically had been experienced in the enterprise in nearly every industry. This has been especially problematic in the medical and manufacturing fields. As the attackers saturate the specifically targeted industries, the attackers will expand their target industries. One of these which has not been significantly explored by the ransomware groups are the embedded systems and automobile environment. This set of targets is massive and provides for a vast attack potential. While this has not experienced this attack methodology at length, the research and efforts are creeping towards this as a natural extension of the business. The research focusses on the history of ransomware, uses in the enterprise, possible attack vectors with ground vehicles, and defenses to be explored and implemented to secure automobiles, fleets, and the industries.

In this paper, we outline past, present and future applications of automotive security for engine ECUs. Electronic immobilizers and anti-tuning countermeasures have been used for several years. Recently, OEMs and suppliers are facing more and more powerful attackers, and as a result, have introduced stronger countermeasures based on hardware security. Finally, with the advent of connected cars, it is expected that many things that currently require a physical connection will be done remotely in a near future. This includes remote diagnostics, reprogramming and engine calibration.

Additional complicating factors, such as cybersecurity concerns combined with a first responder’s legal authority, may pose challenges for traditional data collection.

Automotive system functionalities spread over a wide range of sub-domains ranging from non-driving related components to complex autonomous driving related components. The requirements to design and develop these components span across software, hardware, firmware, etc. elements. The successful development of these components to achieve the needs from the stockholders requires accurate understanding and traceability of the requirements of these component systems. The high-level customer requirements transformation into low level granularity requires an efficient requirement engineer. The manual understanding of the customer requirements from the requirement documents are influenced by the context and the knowledge gap of the requirement engineer in understanding and transforming the requirements.

Autonomous vehicles might one day be able to implement privacy preserving driving patterns which humans may find too difficult to implement. In order to measure the difference between location privacy achieved by humans versus location privacy achieved by autonomous vehicles, this paper measures privacy as trajectory anonymity, as opposed to single location privacy or continuous privacy. This paper evaluates how trajectory privacy for randomized driving patterns could be twice as effective for autonomous vehicles using diverted paths compared to Google Map API generated shortest paths. The result shows vehicles mobility patterns could impact trajectory and location privacy. Moreover, the results show that the proposed metric outperforms both K-anonymity and KDT-anonymity.

In conjunction with an increasing number of related laws and regulations (such as UNECE R155 and ISO 21434), these drive security requirements in different domains and areas. 2 In this paper we examine the upcoming trends in EE architectures and investigate the underlying cyber-security threats and corresponding security requirements that lead to potential requirements for “Automotive Embedded Hardware Trust Anchors” (AEHTA).

The paper includes a description of cybersecurity measures to protect the vehicle against malicious attacks.

With the rapid development of connected and autonomous vehicles, more sophisticated automotive systems running large portions of software and implementing a variety of communication interfaces are being developed. The ever-expanding codebase increases the risk for software vulnerabilities, while at the same time the large number of communication interfaces make the systems more susceptible to be targeted by attackers. As such, it is of utmost importance for automotive organizations to identify potential vulnerabilities early and continuously in the development lifecycle in an automated manner. In this paper, we suggest a practical approach for integrating fuzz testing into a Continuous Integration (CI) pipeline for automotive systems. As a first step, we have performed a Threat Analysis and Risk Assessment (TARA) of a general E/E architecture to identify high-risk interfaces and functions.

The caveat to these additional capabilities is issues like cybersecurity, complexity, etc. This paper is an exploration into FuSa and CAVs and will present a systematic approach to understand challenges and propose potential framework, Intelligent Vehicle Monitoring for Safety and Security (IVMSS) to handle faults/malfunctions in CAVs, and specifically autonomous systems.

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.

Vehicle cybersecurity consists of internal security and external security. Dedicated security hardware will play an important role in car’s internal and external security communication. ...For certain AURIX MCU consisting of HSM, the experiment result shows that cheaper 32-bit HSM’s AES calculating speed is 25 times of 32-bit main controller, so HSM is an effective choice to realize cybersecurity. After comparing two existing methods that realize secure CAN communication, A Modified SECURE CAN scheme is proposed, and differences of the three schemes are analyzed.

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

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.

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.