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It delivers details on key subject areas including: • SAE International Standard J3061; the cybersecurity guidebook for cyber-physical vehicle systems • The differences between automotive and commercial vehicle cybersecurity. • Forensics for identifying breaches in cybersecurity. • Platooning and fleet implications. • Impacts and importance of secure systems for today and for the future. ...This book provides a thorough view of cybersecurity to encourage those in the commercial vehicle industry to be fully aware and concerned that their fleet and cargo could be at risk to a cyber-attack. ...It delivers details on key subject areas including: • SAE International Standard J3061; the cybersecurity guidebook for cyber-physical vehicle systems • The differences between automotive and commercial vehicle cybersecurity. • Forensics for identifying breaches in cybersecurity. • Platooning and fleet implications. • Impacts and importance of secure systems for today and for the future.

Their associated information technology and cyber physical systems—along with an exponentially resultant number of interconnections—present a massive cybersecurity challenge. Unlike the physical security challenge, which was treated in earnest throughout the last decades, cyber-attacks on airports keep coming, but most airport lack essential means to confront such cyber-attacks. ...These missing means are not technical tools, but rather holistic regulatory directives, technical and process standards, guides, and best practices for airports cybersecurity—even airport cybersecurity concepts and basic definitions are missing in certain cases. Unsettled Topics Concerning Airport Cybersecurity Standards and Regulation offers a deeper analysis of these issues and their causes, focusing on the unique characteristics of airports in general, specific cybersecurity challenges, missing definitions, and conceptual infrastructure for the standardization and regulation of airports cybersecurity. ...Unsettled Topics Concerning Airport Cybersecurity Standards and Regulation offers a deeper analysis of these issues and their causes, focusing on the unique characteristics of airports in general, specific cybersecurity challenges, missing definitions, and conceptual infrastructure for the standardization and regulation of airports cybersecurity.

Day by day, airports adopt more IoT devices. However, airports are not exempt from possible failures due to malware’s proliferation that can abuse vulnerabilities. Computer criminals can access, corrupt, and extract information from individuals or companies. This paper explains the development of a propagation model, which started with a Delphi process. We discuss the preliminary implications for airports of the simulation model built from the Delphi recommendations.

Special guest Kirsten Koepsel, lawyer and engineer specializing in cyber security, talks with SAE International about how this new environment affects the planes and airports we use every day.

The results of this work is allowed to identify a number of cybersecurity threats of the automated security-critical automotive systems, which reduces the efficiency of operation, road safety and system safety. ...According to the evaluating criterion of board electronics, the presence of poorly-protected communication channels, the 75% of the researched modern vehicles do not meet the minimum requirements of cybersecurity due to the danger of external blocking of vital systems. The revealed vulnerabilities of the security-critical automotive systems lead to the necessity of developing methods for mechanical and electronic protection of the modern vehicle. ...The law of normal distribution of the mid-points of the expert evaluation of the cyber-security of a modern vehicle has been determined. Based on the system approach, ranking of the main cybersecurity treats is performed.

The global time that is propagated and synchronized in vehicle E/E architecture is used in safety-critical, security-critical and time-critical applications. The cybersecurity attacks on the global time result in false time, accuracy degradation and DoS as stated in IETF RFC 7384.

From hydrogen-fueled buses to AI-driven advancements and cybersecurity, this book offers an unparalleled glimpse into the future of transit. Navigate the complexities of transit planning in a post-COVID world, where innovative solutions are essential to tackle infrastructure challenges and workforce shortages.

Abstract “It cannot happen to us” is one of many common myths regarding cybersecurity in the transportation industry. The traditional view that the threats to transportation are low probability and low impact keep agencies from mitigating security threats to transportation critical infrastructure.

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.

As well, functional safety and cybersecurity constraints will increase. Electrification implies replacing energy from thermal sources with electricity from the wall and will include enhanced integration between sub-systems and components, along with higher speed in real time controls.

SAE is developing a number of standards, including the SAE J2945/x and SAE J3161/x series, that specify a set of applications using message sets from the SAE J2735 data dictionary. (“Application” is used here to mean “a collection of activities including interactions between different entities in the service of a collection of related goals and associated with a given IEEE Provider Service Identifier (PSID)”). Authenticity and integrity of the communications for these applications are ensured using digital signatures and IEEE 1609.2 digital certificates, which also indicate the permissions of the senders using Provider Service Identifiers (PSIDs) and Service Specific Permissions (SSPs). The PSID is a globally unique identifier associated with an application specification that unambiguously describes how to build interoperable instances of that application.

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.

Abstract Connected vehicle technology consisting of Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication falls under the umbrella of V2X, or Vehicle-to-Everything, communication. This enables vehicles and infrastructure to exchange safety-related information to enable smarter, safer roads. If driver alerts are raised or automated action is taken as a result of these messages, it is critical that messages are trustworthy and reliable. To this end, the Security Credential Management System (SCMS) and Cooperative Intelligent Transportation Systems (C-ITS) Credential Management System (CCMS) have been proposed to enable authentication and authorization of V2X messages without compromising individual user privacy. This is accomplished by issuing each vehicle a large set of “pseudonyms,” unrelated to any real-world identity. During operation, the vehicle periodically switches pseudonyms, thereby changing its identity to others in the network.

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.

In the past, research on blockchain technology has addressed security and privacy concerns within intelligent transportation systems for critical V2I and V2V communications that form the backbone of Internet of Vehicles. Within trucking industry, a recent trend has been observed towards the use of blockchain technology for operations. Industry stakeholders are particularly looking forward to refining status quo contract management and vehicle maintenance processes through blockchains. However, the use of blockchain technology for enhancing vehicle performance in fleets, especially while considering the fact that modern-day intelligent vehicles are prone to cyber security threats, is an area that has attracted less attention. In this paper, we demonstrate a case study that makes use of blockchains to securely optimize the fuel economy of fleets that do package pickup and delivery (P&D) in urban areas.

Abstract Connected vehicles and intelligent transportation systems are currently evolving into highly interconnected digital environments. Due to the interconnectivity of different systems and complex communication flows, a joint risk analysis for combining safety and security from a system perspective does not yet exist. We introduce a novel method for joint risk assessment in the automotive sector as a combination of the Diamond Model, Failure Mode and Effects Analysis (FMEA), and Factor Analysis of Information Risk (FAIR). These methods have been sequentially composed, which results in a comprehensive risk management approach to information security in an intelligent transport system (ITS). The Diamond Model serves to identify and structurally describe threats and scenarios, the widely accepted FMEA provides threat analysis by identifying possible error combinations, and FAIR provides a quantitative estimation of probabilities for the frequency and magnitude of risk events.

Connected vehicles can provide data from multiple sensors that monitor both the vehicle and the environment through which the vehicle is passing. The data, when shared, can be used to enhance and optimize transportation operations and management—specifically, traffic flow and infrastructure maintenance. This document describes an interface between vehicle and infrastructure for collecting vehicle/probe data. That data may represent a single point in time or may be accumulated over defined periods of time or distance, or may be triggered based on circumstance. The purpose of this document is to define an interoperable means of collecting the vehicle/probe data in support of the use cases defined herein. There are many additional use cases that may be realized based on the interface defined in this document. Note that vehicle diagnostics are not included within the scope of this document, but diagnostics-related features may be added to probe data in a future supplemental document.

Editorial High noon for high-level autonomy The Navigator A fork in the road for the AV business The Electric, Autonomous Revolution Lifts Off Engineering the new generation of electric and hybrid vertical-take-off-and-landing vehicles at Wisk and Elroy Air. New SAE Standard for Automated-Driving Developers Developed in less than a year, SAE's new J3216 standard will impact traffic management, operations and safety for automated mobility. Making Data Logging, Replay and Prototyping More Efficient High levels of continuity and compatibility are vital to avoid interruptions in the development process - and reduce cost. Radar Death Star ELunewave's 3D-printed spherical antenna makes for fast, 360-degree single-snapshot readings that are claimed to beat the slower sweeps of conventional radar. The Case for FOTA in AV Data Security Firmware over-the-air data transmission helps OEMs drive secure vehicle autonomy.

Abstract With the adoption of Vehicle-to-everything (V2X) technology, security and privacy of vehicles are paramount. To avoid tracking while preserving vehicle/driver’s privacy, modern vehicular public key infrastructure provision vehicles with multiple short-term pseudonym certificates. However, provisioning a large number of pseudonym certificates can lead to an enormous growth of Certificate Revocation Lists (CRLs) during its revocation process. One possible approach to avoid such CRL growth is by relying on activation code (AC)-based solutions. In such solutions, the vehicles are provisioned with batches of encrypted certificates, which are decrypted periodically via the ACs (broadcasted by the back-end system). When the system detects a revoked vehicle, it simply does not broadcast the respective vehicle’s AC. As a result, revoked vehicles do not receive their respective AC and are prevented from decrypting their certificates.

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.