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Connected commercial vehicles bring cybersecurity to the fore Connectivity, automation and electrification will largely drive vehicle developments in the coming years, according to experts presenting at the revamped SAE COMVEC 17.

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 EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

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.

SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

This document will provide recommendations to vehicle manufacturers and component suppliers in securing the SAE J1939-13 connector interface from the cybersecurity risks posed by the existence of this connector.

Do you know what personal protective equipment (PPE), tools, and instruments are needed to keep you safe around high voltage (HV) vehicles? Are you aware of how to protect yourself or your employees when working around high voltage systems and platforms? Safety is paramount when working around any type of high voltage. As electric vehicles (EV) and EV fleets become more prevalent, the critical need for OEMs, suppliers, companies, and organizations to provide comprehensive safety training for teams working with or around xEV systems and platforms increases.

This document will provide recommendations to vehicle manufacturers and component suppliers in securing the SAE J1939 network from the cybersecurity risks. It is recognized that not every application of SAE J1939 networks requires the same level of cyber security measures.

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.

With the rapid development of vehicle intelligent and networking technology, the IT security of automotive systems becomes an important area of research. In addition to the basic vehicle control, intelligent advanced driver assistance systems, infotainment systems will all exchange data with in-vehicle network. Unfortunately, current communication network protocols, including Controller Area Network (CAN), FlexRay, MOST, and LIN have no security services, such as authentication or encryption, etc. Therefore, the vehicle are unprotected against malicious attacks. Since CAN bus is actually the most widely used field bus for in-vehicle communications in current automobiles, the security aspects of CAN bus is focused on. Based on the analysis of the current research status of CAN bus network security, this paper summarizes the CAN bus potential security vulnerabilities and the attack means.

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).

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.

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.

This SAE Information Report J2931/7 establishes the security requirements for digital communication between Plug-In Electric Vehicles (PEV), the Electric Vehicle Supply Equipment (EVSE) and the utility, ESI, Advanced Metering Infrastructure (AMI) and/or Home Area Network (HAN).

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.

This document describes a set of recommended actions to take to increase the likelihood of safe vehicle operation when a device (external test equipment, data collection device, etc.) whose normal operation has been compromised by a source external to the vehicle is connected to the vehicle’s diagnostic system. The term “diagnostic system” is intended to be a generic way to reference all the different ways that diagnostic commands might be injected into the system. The guidance in this document is intended to improve security without significantly impacting the ability for franchised dealer or independent aftermarket external test tools to perform legitimate diagnosis and maintenance functions. The goal is that intrusive services are only allowed to be performed when the vehicle is in a Safe State such that even if the intrusive service were to be initiated with adversarial intent the consequences of such a service would still be acceptable.

Cyber assurance of heavy trucks is a major concern with new designs as well as with supporting legacy systems. Many cyber security experts and analysts are used to working with traditional information technology (IT) networks and are familiar with a set of technologies that may not be directly useful in the commercial vehicle sector. To help connect security researchers to heavy trucks, a remotely accessible testbed has been prototyped for experimentation with security methodologies and techniques to evaluate and improve on existing technologies, as well as developing domain-specific technologies. The testbed relies on embedded Linux-based node controllers that can simulate the sensor inputs to various heavy vehicle electronic control units (ECUs). The node controller also monitors and affects the flow of network information between the ECUs and the vehicle communications backbone.

This SAE Information Report J2836 establishes the instructions for the documents required for the variety of potential functions for PEV communications, energy transfer options, interoperability and security. This includes the history, current status and future plans for migrating through these documents created in the Hybrid Communication and Interoperability Task Force, based on functional objective (e.g., (1) if I want to do V2G with an off-board inverter, what documents and items within them do I need, (2) What do we intend for V3 of SAE J2953, …).

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.