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What standardization is needed to ensure that quantum technologies do not pose an unacceptable risk from an automotive cybersecurity perspective? Click here to access the full SAE EDGETM Research Report portfolio.

Argus, a global leader in automotive cybersecurity, has upgraded its stand-alone Fleet Protection backend platform and is now providing continuous live monitoring of both automotive and commercial aircraft fleets.

Automotive cybersecurity issues are becoming more prominent than ever. SAE J3061 and ISO/SAE 21434 being drafted also indicate that automotive cybersecurity has been elevated to a position equal to or more important than functional safety. ...SAE J3061 and ISO/SAE 21434 being drafted also indicate that automotive cybersecurity has been elevated to a position equal to or more important than functional safety. ...Security threat analysis helps the development of the early concept phase of automotive cybersecurity. However, the threat analysis based on the traditional attack tree has the disadvantages of multiple subjective factors and low accuracy.

IOOs and ADS developers agree that cost, communications, interoperability, cybersecurity, operation, maintenance, and other issues undercut efforts to deploy a comprehensive connected infrastructure.

Using a wireless medium for tractor-trailer communication will bring new cybersecurity challenges and requirements which requires new development and lifecycle considerations.

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.

Recent developments in the commercialization of mobility services have brought unprecedented connectivity to the automotive sector. While the adoption of connected features provides significant benefits to vehicle owners, adversaries may leverage zero-day attacks to target the expanded attack surface and make unauthorized access to sensitive data. Protecting new generations of automotive controllers against malicious intrusions requires solutions that do not depend on conventional countermeasures, which often fall short when pitted against sophisticated exploitation attempts. In this paper, we describe some of the latent risks in current automotive systems along with a well-engineered multi-layer defense strategy. Further, we introduce a novel and comprehensive attack and performance test framework which considers state-of-the-art memory corruption attacks, countermeasures and evaluation methods.

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.

Abstract This work introduces the concept of a dual-layer specification structure for standards that separate interoperability functions, such as backward compatibility, localization, and deployment, from those essential to reliability, security, and functionality. The latter group of features, which constitute the actual standard, make up the baseline layer for instructions, while all the elements required for interoperability are specified in a second layer, known as a Protocols, Operations, Usage, and Formats (POUF) document. We applied this technique in the development of a standard for Uptane [1], a security framework for over-the-air (OTA) software updates used in many automobiles. This standard is a good candidate for a dual-layer specification because it requires communication between entities, but does not require a specific format for this communication.

To help address the issue of message authentication on the Controller Area Network (CAN) bus, researchers at Virginia Tech and Ford Motor Company have developed a proof-of-concept time-evolving watermark-based authentication mechanism that offers robust, cryptographically controlled confirmation of a CAN message's authenticity. This watermark is injected as a common-mode signal on both CAN-HI and CAN-LO bus voltages and has been proven using a low-cost software-defined radio (SDR) testbed. This paper extends prior analysis on the design and proof-of-concept to consider robustness testing over the range of voltages, both steady state drifts and transients, as are commonly witnessed within a vehicle. Overall performance results, along with a dynamic watermark amplitude control, validate the concept as being a practical near-term approach at improving authentication confidence of messages on the CAN bus.

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.

Abstract The rapid development of connected and automated vehicle technologies together with cloud-based mobility services is transforming the transportation industry. As a result, huge amounts of consumer data are being collected and utilized to provide personalized mobility services. Using big data poses serious challenges to data privacy. To that end, the risks of privacy leakage are amplified by data aggregations from multiple sources and exchanging data with third-party service providers, in face of the recent advances in data analytics. This article provides a review of the connected vehicle landscape from case studies, system characteristics, and dataflows. It also identifies potential challenges and countermeasures.

Abstract Vehicular communications face unique security issues in wireless communications. While new vehicles are equipped with a large set of communication technologies, product life cycles are long and software updates are not widespread. The result is a host of outdated and unpatched technologies being used on the street. This has especially severe security impacts because autonomous vehicles are pushing into the market, which will rely, at least partly, on the integrity of the provided information. We provide an overview of the currently deployed communication systems and their security weaknesses and features to collect and compare widely used security mechanisms. In this survey, we focus on technologies that work in an ad hoc manner. This includes Long-Term Evolution mode 4 (LTE-PC5), Wireless Access in Vehicular Environments (WAVE), Intelligent Transportation Systems at 5 Gigahertz (ITS-G5), and Bluetooth.

Abstract In the pursuit of advancing autonomous vehicles (AVs), data-driven algorithms have become pivotal in replacing human perception and decision-making. While deep neural networks (DNNs) hold promise for perception tasks, the potential for catastrophic consequences due to algorithmic flaws is concerning. A well-known incident in 2016, involving a Tesla autopilot misidentifying a white truck as a cloud, underscores the risks and security vulnerabilities. In this article, we present a novel threat model and risk assessment (TARA) analysis on AV data storage, delving into potential threats and damage scenarios. Specifically, we focus on DNN parameter manipulation attacks, evaluating their impact on three distinct algorithms for traffic sign classification and lane assist.

As an annual subscription, the Wiley Cyber Security Collection Add-On is available for purchase along with one or both of the following: Wiley Aerospace Collection Wiley Automotive Collection The titles from the Wiley Cyber Security Collection are included in the SAE MOBILUS® eBook Package. Titles: Network Forensics Penetration Testing Essentials Security in Fixed and Wireless Networks, 2nd Edition The Network Security Test Lab: A Step-by-Step Guide Risk Centric Threat Modeling: Process for Attack Simulation and Threat Analysis Applied Cryptography: Protocols, Algorithms and Source Code in C, 20th Anniversary Edition Computer Security Handbook, Set, 6th Edition Threat Modeling: Designing for Security Other available Wiley collections: Wiley SAE MOBILUS eBook Package Wiley Aerospace Collection Wiley Automotive Collection Wiley Computer Systems Collection Add-On (purchasable with the Wiley Aerospace Collection and/or the Wiley Automotive Collection)

Digitally enabled mobility vehicles and services, including dockless bikesharing and electric scooter sharing, are generating and collecting a growing amount of mobility data. Mobility data holds great potential to support transportation officials and their efforts to manage the public right-of-way, but the unlimited distribution of mobility data carries untested risks to privacy and public trust. The Mobility Data Collaborative™ has identified the need to improve and coordinate understanding among all parties around foundational policy and legal issues to support mobility data sharing, including privacy and contracting. The guidelines are geared towards supporting a scalable mobility data sharing framework that aligns the interests of the public and private sectors while addressing privacy, transparency, data ownership, and consumer trust.

Editorial V2Reality Blockchain Unchained! The weird world of cryptocurrency exists because of the intense mathematics of blockchain technology. The mobility sector is looking beyond Bitcoin to put blockchain to work in potentially game-changing ways. Are Blockchain and 'Smart Contracts' the Secure Future? Legal risk and reward of blockchain and smart contracts as a prescription for automotive applications Software Building Blocks for AV Systems Elektrobit's unique software framework is designed to smooth development of automated driving functions. Cyber Security Goes Upstream The first cloud-based solution for connected vehicles was born in Israel and is now pilot testing at global OEMs. Electronic Architectures Get Smart Upgradable, scalable and powerful new architectures will help enable data-hungry connected, autonomous vehicles. Aptiv's VP of Mobility Architecture explains.

Rethinking the HUD Advanced tech solutions move toward augmented reality to bring greater capability to head-up displays. Motor matters New designs and materials are key to the next generation of electric machines for EV propulsion. Harnessing the power of Sim Serious cost savings could come from eliminating vehicle- and systems-level tests. Powerful simulation tools may be the only way to tackle the increasing complexity in mobility development. An OBE for the SAE Meet Paul Mascarenas-SAE International's 2019 president. He's a staunch advocate for professional development for engineers amid the mobility industry's transformation. Solving the propulsion puzzle Must-attend expert panels at SAE's WCX '19 will cover the propulsion-tech future like no other. Editorial Kill the EV tax credit by 2025 SAE Standards News SAE and Synopsys collaborate on cyber study Supplier Eye New Co. vs. Old Co.

Editorial The consolidation plot thickens The Navigator As the world turns to C-V2X, Europe picks WiFi Complexity of Autonomous-Systems Simulation, Validation Soars to the Clouds Scalable, cloud-based architectures are gaining greater acceptance for simulating and testing the myriad development aspects of automated driving. Connectivity Solutions for AVs The promises of fully connected autonomous vehicles are great, but so are the challenges. What M&E Can Teach the AV Industry About Data Media & entertainment offers important learnings on data retention, management, scalability and security. The Rodney Dangerfield of Automated-Driving Sensors Radar and lidar get all the attention, but Inertial Measurement Units are the backbone of sensor fusion. Suppliers are scrambling to make IMUs more accurate-and much less expensive. The Sense-itive Side of Autonomous Vehicles BASF is exploring how specific materials-and even paint colors and finishes-can improve the capabilities of AV sensors.

Editorial Fool Self-Driving II The Navigator What will result from NHTSA's Tesla Autopilot investigation? Data Drives Driverless Truck Launch Smart diagnostics and advanced validation help support the reliability metrics required to gain confidence that autonomous trucks are ready for the road. Peering into the Distance New sensors of all types look out longer distances - and provide higher resolutions - for engineers pushing ADAS capabilities and higher-level vehicle automation. Ford Drives into SAE Level 2 Driver monitoring was an essential component to engineering the new "hands-free" BlueCruise/Active Glide enhanced ADAS system. A Chore No More? The Detroit Smart Parking Lab opens to develop and test emerging parking technology in real-world settings. Share and Share Alike The concepts of rideshare and urban mobility continue to evolve as new projects test what's possible.