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The hypervisor offers many benefits to the vehicle architecture, both operationally and with cybersecurity. The proposed mitigant provides the structure to partition the various VMs. This allows for the different functions to be managed within their own distinct VM. ...While the cybersecurity applications are numerous, there are also the operational benefits. The hypervisor is designed to not only manage the VMs, but also to increase the efficiency of these via resource management.

Symbolic code execution is a powerful cybersecurity testing approach that facilitates the systematic exploration of all paths within a program to uncover previously unknown cybersecurity vulnerabilities. ...Symbolic code execution is a powerful cybersecurity testing approach that facilitates the systematic exploration of all paths within a program to uncover previously unknown cybersecurity vulnerabilities. This is achieved through a Satisfiability Modulo Theory (SMT) solver, which operates on symbolic values for program inputs instead of using their concrete counterparts.

This method's detailed approach ensures that cybersecurity requirements can be readily implemented as a part of feature design, addressing the concerns of feature owners directly. ...This paper will discuss the merits of asset based approach to cybersecurity over attack based recognizing the inherent strengths and limitations of both methods and underscores the need for a unified approach.

., driver assistance functions, intrusion detection system, vehicle diagnostics, external device authentication during vehicle diagnostics, vehicle-to-grid and so on). The cybersecurity attacks targeting the global time result in false time, accuracy degradation, and denial of service as stated in IETF RFC 7384.

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

The article also focus on innovative approaches that have recently adopted my many cybersecurity professionals for secured operation of ITS involving block-chain, artificial intelligence, and Machine Learning.

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).

On-road vehicles equipped with driving automation features—where a human might not be needed for operation on-board—are entering the mainstream public space. However, questions like “How safe is safe enough?” and “What to do if the system fails?” persist. This is where remote operation comes in, which is an additional layer to the automated driving system where a human remotely assists the so-called “driverless” vehicle in certain situations. Such remote-operation solutions introduce additional challenges and potential risks as the entire vehicle-network-human now needs to work together safely, effectively, and practically. Unsettled Issues in Remote Operation for On-road Driving Automation highlights technical questions (e.g., network latency, bandwidth, cyber security) and human aspects (e.g., workload, attentiveness, situational awareness) of remote operation and introduces evolving solutions.

The UN R155 regulation is the first automotive cyber security regulation and has made security a mandatory approval criterion for new vehicle types. This establishes internationally harmonized security requirements for market approval. As a result, the application of the regulation presents manufacturers and suppliers with the challenge of demonstrating compliance. At process level the implementation of a Cyber Security Management System (CSMS) is required while at product level, the Threat Assessment and Risk Analysis (TARA) forms the basis to identify relevant threats and corresponding mitigation strategies. Overall, an issued type approval is internationally recognized by the member states of the UN 1958 Agreement. International recognition implies that uniform assessment criteria are applied to demonstrate compliance and to decide whether security efforts are sufficient.

Driven by the growing internet and remote connectivity of automobiles, combined with the emerging trend to automated driving, the importance of security for automotive systems is massively increasing. Although cyber security is a common part of daily routines in the traditional IT domain, necessary security mechanisms are not yet widely applied in the vehicles. At first glance, this may not appear to be a problem as there are lots of solutions from other domains, which potentially could be re-used. But substantial differences compared to an automotive environment have to be taken into account, drastically reducing the possibilities for simple reuse. Our contribution is to address automotive electronics engineers who are confronted with security requirements. Therefore, it will firstly provide some basic knowledge about IT security and subsequently present a selection of automotive specific security use cases.

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.

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.

This paper is the second in the series of documents designed to record the progress of a series of SAE documents - SAE J2836™, J2847, J2931, & J2953 - within the Plug-In Electric Vehicle (PEV) Communication Task Force. This follows the initial paper number 2010-01-0837, and continues with the test and modeling of the various PLC types for utility programs described in J2836/1™ & J2847/1. This also extends the communication to an off-board charger, described in J2836/2™ & J2847/2 and includes reverse energy flow described in J2836/3™ and J2847/3. The initial versions of J2836/1™ and J2847/1 were published early 2010. J2847/1 has now been re-opened to include updates from comments from the National Institute of Standards Technology (NIST) Smart Grid Interoperability Panel (SGIP), Smart Grid Architectural Committee (SGAC) and Cyber Security Working Group committee (SCWG).

As an important part of intelligent driving vehicles and intelligent networked transportation systems, environmental perception technology can provide important decision-making basis for the overall planning of intelligent driving vehicles and transportation systems. This paper reviews the current research on environment perception technology in the current intelligent networked transportation system, and analyzes four key research directions and related progress of environmental sensing technologies, including single sensor device, high-precision map, multi-sensor information fusion and vehicle-road collaboration. On the basis of analyzing and summarizing existing related research, this article elaborates the development trend and key directions of future environmental perception technology, including the integration of deep learning, vehicle-road integration, information security and multi-dimensional perception technology related development directions.

Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.

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.

Cyber security is becoming increasingly critical in the car industry. Not only the entry points to the external world in the car need to be protected against potential attack, but also the on-board communication in the car require to be protected against attackers who may try to send unauthorized CAN messages. However, the current CAN network was not designed with security in mind. As a result, the extra measures have to be taken to address the key security properties of the secure CAN communication, including data integrity, authenticity, confidentiality and freshness. While integrity and authenticity can be achieved by using a relatively straightforward algorithms such as CMAC (Cipher-based Message Authentication Code) and Confidentiality can be handled by a symmetric encryption algorithm like AES128 (128-bit Advanced Encryption Standard), it has been recognized to be more challenging to achieve the freshness of CAN message.

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.

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.

The new generation vehicles these days are managed by networked controllers. A large portion of the networks is planned with more security which has recently roused researchers to exhibit various attacks against the system. This paper talks about the liabilities of the Controller Area Network (CAN) inside In-vehicle communication protocol and a few potentials that could take due advantage of it. Moreover, this paper presents a few security measures proposed in the present examination status to defeat the attacks. In any case, the fundamental objective of this paper is to feature a comprehensive methodology known as Intrusion Detection System (IDS), which has been a significant device in getting network data in systems over many years. To the best of our insight, there is no recorded writing on a through outline of IDS execution explicitly in the CAN transport network system.