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COMVEC™ conference is the only North American event that addresses vehicles and equipment spanning on-highway, off-highway, agricultural, construction, industrial, military, and mining sectors.

Abstract Identity-Anonymized CAN (IA-CAN) protocol is a secure CAN protocol, which provides the sender authentication by inserting a secret sequence of anonymous IDs (A-IDs) shared among the communication nodes. To prevent malicious attacks from the IA-CAN protocol, a secure and robust system error recovery mechanism is required. This article presents a central management method of IA-CAN, named the IA-CAN with a global A-ID, where a gateway plays a central role in the session initiation and system error recovery. Each ECU self-diagnoses the system errors, and (if an error happens) it automatically resynchronizes its A-ID generation by acquiring the recovery information from the gateway. We prototype both a hardware version of an IA-CAN controller and a system for the IA-CAN with a global A-ID using the controller to verify our concept.

Abstract In the automotive domain, the overall complexity of technical components has increased enormously. Formerly isolated, purely mechanical cars are now a multitude of cyber-physical systems that are continuously interacting with other IT systems, for example, with the smartphone of their driver or the backend servers of the car manufacturer. This has huge security implications as demonstrated by several recent research papers that document attacks endangering the safety of the car. However, there is, to the best of our knowledge, no holistic overview or structured description of the complex automotive domain. Without such a big picture, distinct security research remains isolated and is lacking interconnections between the different subsystems. Hence, it is difficult to draw conclusions about the overall security of a car or to identify aspects that have not been sufficiently covered by security analyses.

With the development of vehicle intelligence and the Internet of Vehicles, how to protect the safety of the vehicle network system has become a focus issue that needs to be solved urgently. The Controller Area Network (CAN) bus is currently a very widely used vehicle-mounted bus, and its security largely determines the degree of vehicle-mounted information security. The CAN bus lacks adequate protection mechanisms and is vulnerable to external attacks such as replay attacks, modifying attacks, and so on. On the basis of the existing work, this paper proposes an authentication method that combines Hash-based Message Authentication Code (HMAC)-SHA256 and Tiny Encryption Algorithm (TEA) algorithms. This method is based on dynamic identity authentication in challenge/response made and combined with the characteristics of the CAN bus itself as it achieves the identity authentication between the gateway and multiple electronic control units (ECUs).

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.

Abstract The innovations of vehicle connectivity have been increasing dramatically to enhance the safety and user experience of driving, while the rising numbers of interfaces to the external world also bring security threats to vehicles. Many security countermeasures have been proposed and discussed to protect the systems and services against attacks. To provide an overview of the current states in this research field, we conducted a systematic mapping study (SMS) on the topic area “security countermeasures of in-vehicle communication systems.” A total of 279 papers are identified based on the defined study identification strategy and criteria. We discussed four research questions (RQs) related to the security countermeasures, validation methods, publication patterns, and research trends and gaps based on the extracted and classified data. Finally, we evaluated the validity threats and the whole mapping process.

Since the early 1990’s, commercial vehicles have suffered from repeated vulnerability exploitations that resulted in a need for improved automotive cybersecurity. This paper outlines the strategies and challenges of implementing an automotive Zero Trust Architecture (ZTA) to secure intra-vehicle networks. ...This research successfully met the four requirements and demonstrated that using ZT principles in an on-vehicle network greatly improved the cybersecurity posture with manageable impact to system performance and deployment.

Abstract Secure boot is a fundamental security primitive for establishing trust in computer systems. For real-time safety applications, the time taken to perform the boot measurement conflicts with the need for near instant availability. To speed up the boot measurement while establishing an acceptable degree of trust, we propose a dual-phase secure boot algorithm that balances the strong requirement for data tamper detection with the strong requirement for real-time availability. A probabilistic boot measurement is executed in the first phase to allow the system to be quickly booted. This is followed by a full boot measurement to verify the first-phase results and generate the new sampled space for the next boot cycle. The dual-phase approach allows the system to be operational within a fraction of the time needed for a full boot measurement while producing a high detection probability of data tampering.

But unfortunately, automotive cybersecurity researchers hardly produce a comprehensive detection method due to the confidential nature of Controller Area Network (CAN) DBC format files, which is a standard long maintained by car manufacturers.

Abstract The automotive industry intends to create new services that involve sharing vehicle control information via a wide area network. In modern vehicles, an in-vehicle network shares information between more than 70 electronic control units (ECUs) inside a vehicle while it is driven. However, such a complicated system configuration can result in security vulnerabilities. The possibility of cyber-attacks on vehicles via external services has been demonstrated in many research projects. As advances in vehicle systems (e.g., autonomous drive) progress, the number of vulnerabilities to be exploited by cyber-attacks will also increase. Therefore, future vehicles need security measures to detect unknown cyber-attacks. We propose anomaly-based intrusion detection to detect unknown cyber-attacks for the Control Area Network (CAN) protocol, which is popular as a communication protocol for in-vehicle networks.

In adjusting the data flow, this is an option to increase the cybersecurity for a complete system. This addition to the cybersecurity system provides a clear benefit. ...While this is the traditional application experienced, there are other applications relevant to cybersecurity. As part of the blockchain technology, the nodes are responsible for decision-making.

Abstract Over the past forty years, the Electronic Control Unit (ECU) technology has grown in both sophistication and volume in the automotive sector, and modern vehicles may comprise hundreds of ECUs. ECUs typically communicate via a bus-based network architecture to collectively support a broad range of safety-critical capabilities, such as obstacle avoidance, lane management, and adaptive cruise control. However, this technology evolution has also brought about risks: if ECU firmware is compromised, then vehicle safety may be compromised. Recent experiments and demonstrations have shown that ECU firmware is not only poorly protected but also that compromised firmware may pose safety risks to occupants and bystanders.

Innovations for lightweighting Tough fuel-economy bogies for 2021 and beyond are driving new approaches to materials use, as seen in these case studies. Axellent progress AAM's new Quantum drive-axle technology is a leap forward in lightweight, efficient driveline systems aimed at 2020 and beyond. Low-temperature combustion ready for prime time? At SAE's High-Efficiency IC Engines Symposium, Delphi said its new, third-generation GDCI is promising, but even LTC proponents admit that challenges remain. More automation for ECU testing The latest fault-insertion tests enable engineers to run more test cases in less time.

New vision @ Gentex Creating a vital ADAS partner through home-grown R&D and manufacturing in (of all places) western Michigan. Positioning for hybrid growth BorgWarner "modularizes" to provide OEMs optimal electrified-driveline flexibility. Editorial: Beleaguered diesel could use a break-or a breakthrough SAE Standards News Kickoff to begin testing program to validate SAE J2954 wireless charging Recommended Practice Supplier Eye Will you be an active participant or passive bystander? The Navigator For future vehicles, communication equals trust Tenneco readies new semi-active digital suspension for 2020 New 90-degree turbo V6 leads Audi's hybridization blitz GKN using modular control algorithms for added systems integration U of M students engineer new autonomous shuttle system Jaguar's 2018 E-Pace shares Land Rover bones Ford pumps powertrains for 2018 F-150 2018 Subaru Crosstrek moves to new global platform Nissan's Ponz Pandikithura on EV lifecycle value

Editorial AV lidar enters a new reality The Navigator UNECE takes first step toward AV regulation Special Delivery - by 'Bot Michigan start-up Refraction AI aims to be the go-to for last-mile, semi-autonomous, all-weather delivery robots. Lidar Infiltrates ADAS Once considered a necessity only in fully autonomous vehicles, lidar sensors are now being evaluated for lower-level driver-assistance systems. Training Data-hungry AI Algorithms Large-scale data refinement is key to bringing more sophisticated automated-driving functions to series production. Simulation's Next Generation Do autonomous-vehicle developers have their simulation strategies all wrong? Some experts think so - but suggest there's a practical solution. Marelli's COVID-killing HVAC Insert With big implications for shared mobility, a new photocatalytic cabin-air purifier claims to kill viruses - including COVID-19. Is Ground-penetrating Radar Next for AV Sensing?

The flexible data rate capability in CAN (commonly called CAN FD) is implemented as a transport layer in order to allow for functional safety, cybersecurity, extended transport capability, and backward compatibility with SAE J1939DA.

The flexible data rate capability in CAN (commonly called CAN FD) is implemented as a transport layer in order to allow for functional safety, cybersecurity, extended transport capability, and backward compatibility with SAE J1939DA.

The flexible data rate capability in CAN (commonly called CAN FD) is implemented as a transport layer in order to allow for functional safety, cybersecurity, extended transport capability, and backward compatibility with SAE J1939DA.

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).