Search Results

An eye-opening Q&A with an impressive panel of experts lays out terrifying cyberattack scenarios including weaponizing EVs and region-wide blackouts.

The project uses PKI to help protect the connection between EVs and charging stations.

Cybersecurity of high-power charging infrastructure for electric vehicles (EVs) is critical to the safety, reliability, and consumer confidence in this publicly accessible technology. ...Cybersecurity of high-power charging infrastructure for electric vehicles (EVs) is critical to the safety, reliability, and consumer confidence in this publicly accessible technology. Cybersecurity vulnerabilities in high-power EV charging infrastructure may also present risks to broader transportation and energy-infrastructure systems. ...This paper details a methodology used to analyze and prioritize high-consequence events that could result from cybersecurity sabotage to high-power charging infrastructure. The highest prioritized events are evaluated under laboratory conditions for the severity of impact and the complexity of cybersecurity manipulation.

Impact of Electric Vehicle Charging on Grid Energy Buffering discusses the unsettled issues and requirements needed to realize the potential of EV batteries for demand response and grid services, such as improved battery management, control strategies, and enhanced cybersecurity. Hybrid and fuel cell EVs have significant potential to act as “peakers” for longer duration buffering, and this approach has the potential to provide all the long-term energy buffering required by a VRE-intensive grid.

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.

October 29-31, 2019 │ Novi, MI

October 29-31, 2019 │ Novi, MI

October 29-31, 2019 │ Novi, MI

Count on SAE International®—the global leader in technical learning for mobility professionals—to deliver emerging research, consumer metrics, regulatory standards and the latest innovations to advance mobility at the WCX World Congress event.

If you are not able to attend WCX 2022 in-person, you will have the opportunity to join a selected number of live technical and executive discussions online that will advance your skill set in propulsion, connectivity security and safety as well as the business of technology.

If you are not able to attend WCX 2022 in-person, you will have the opportunity to join a selected number of live technical and executive discussions online that will advance your skill set in propulsion, connectivity security and safety as well as the business of technology.

Abstract The expansion of the internet has made everyone’s personal and professional lives more transparent. There are network security issues because people like sharing resources under the right conditions. Academics have demonstrated significant interest in situation awareness, which includes situation prediction, situation appraisal, and event detection, rather than focusing on the security of a single device in the network. Multi-stage attack forecasting and security situation awareness are two significant issues for network supervisors because the future usually is unknown. Hence, this study suggests combined intuitionistic fuzzy sets and deep neural network (CIFS-DNN) for network security situation prediction. The goal is to provide network administrators with a resource they can use as a point of reference while they formulate and carry out preventive actions in the event of a network assault.

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).

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, …).

Automotive system functionalities spread over a wide range of sub-domains ranging from non-driving related components to complex autonomous driving related components. The requirements to design and develop these components span across software, hardware, firmware, etc. elements. The successful development of these components to achieve the needs from the stockholders requires accurate understanding and traceability of the requirements of these component systems. The high-level customer requirements transformation into low level granularity requires an efficient requirement engineer. The manual understanding of the customer requirements from the requirement documents are influenced by the context and the knowledge gap of the requirement engineer in understanding and transforming the requirements.

By looking into the vehicle-infrastructure cooperation (VIC) which is oriented towards intelligent, networked and integrated development, this paper analyzes and proposes the essence and development direction of Intelligent Vehicle Infrastructure Cooperation Systems (I-VICS). With an in-depth analysis of technologies of core importance to VIC and influence factors that constrain VIC development as a whole, the paper comes up with a technological route for VIC, and identifies a direction for vehicle-infrastructure cooperative development that progresses from primary to intermediate cooperation, then to advanced cooperation, and finally to full-fledged cooperation. Policy recommendations aiming at strengthening top-level design, building an integrated vehicle-infrastructure-cloud platform, expediting independence of key techs, building robust standards and regulations for VIC, enhancing workforce development as well as greater efforts at market promotion are put forward.

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.