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Here, we discuss the On-Board Diagnostic (OBD) regulations for next generation BEV/HEV, its vulnerabilities and cybersecurity threats that come with hacking. We propose three cybersecurity attack detection and defense methods: Cyber-Attack detection algorithm, Time-Based CAN Intrusion Detection Method and, Feistel Cipher Block Method. ...These control methods autonomously diagnose a cybersecurity problem in a vehicle’s onboard system using an OBD interface, such as OBD-II when a fault caused by a cyberattack is detected, All of this is achieved in an internal communication network structure.

The lack of inherent security controls makes traditional Controller Area Network (CAN) buses vulnerable to Machine-In-The-Middle (MitM) cybersecurity attacks. Conventional vehicular MitM attacks involve tampering with the hardware to directly manipulate CAN bus traffic.

In this paper, we outline past, present and future applications of automotive security for engine ECUs. Electronic immobilizers and anti-tuning countermeasures have been used for several years. Recently, OEMs and suppliers are facing more and more powerful attackers, and as a result, have introduced stronger countermeasures based on hardware security. Finally, with the advent of connected cars, it is expected that many things that currently require a physical connection will be done remotely in a near future. This includes remote diagnostics, reprogramming and engine calibration.

This exercise confirms the necessity of a more restrictive cybersecurity posture in automotive peripherals with access to critical systems, in particular VDAs, and especially when such peripherals present a wireless interface.

The VCE Laboratory testbeds are connected with an Amazon Web Services (AWS) cloud-based Cyber-security Labs as a Service (CLaaS) system, which allows students and researchers to access the testbeds from any place that has a secure internet connection. ...VCE students are assigned predefined virtual machines to perform designated cyber-security experiments. The CLaaS system has low administrative overhead associated with experiment setup and management. ...VCE Laboratory CLaaS experiments have been developed for demonstrating man-in-the-middle cyber-security attacks from actual compromised hardware or software connected with the TestCube.

The scope of the document is to define the cyber-security best practices to reduce interference with normal vehicle operation, or to minimize risk as to unauthorized access of the vehicle's control, diagnostic, or data storage system; access by equipment (i.e., permanently or semi-permanently installed diagnostic communication device, also known as dongle, etc.) which is either permanently or semi-permanently connected to the vehicle's OBD diagnostic connector, either SAE J1939-13, SAE J1962, or other future protocol; or hardwired directly to the in-vehicle network.

Legacy electronic control units are, nowadays, required to implement cybersecurity measures, but they often do not have all the elements that are necessary to realize industry-standard cybersecurity controls. ...Legacy electronic control units are, nowadays, required to implement cybersecurity measures, but they often do not have all the elements that are necessary to realize industry-standard cybersecurity controls. For example, they may not have hardware cryptographic accelerators, segregated areas of memory for storing keys, or one-time programmable memory areas. ...While the UDS service $27 (Security Access) has a reputation for poor cybersecurity, there is nothing inherent in the way it operates which prevents a secure access-control from being implemented.

OBD, J1939 and UDS on CAN / IP), and a glimpse into the near future covering remote, cloud-based diagnostics and cybersecurity threats.

To serve and protect As cars become more connected and automated, cybersecurity concerns are rising. Industry engineers have many tools and techniques and are now deploying encryption and standards to ensure that vehicle controls are not altered or usurped by unauthorized people.

An Holistic Approach to Verifying Cybersecurity in Design A powerful new generation of test and sim solutions aims to address specific security concerns associated with automotive designs.

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

The hypervisor offers many benefits to the vehicle architecture, both operationally and with cybersecurity. The proposed mitigant provides the structure to partition the various VMs. This allows for the different functions to be managed within their own distinct VM. ...While the cybersecurity applications are numerous, there are also the operational benefits. The hypervisor is designed to not only manage the VMs, but also to increase the efficiency of these via resource management.

The paper includes a description of cybersecurity measures to protect the vehicle against malicious attacks.

Innovations in Mobility: Aerospace Digital Summitaerospace mobility leaders convene leverage cutting-edge technology, design, develop safety measures, integrate current regulations, suggest future policies, expand markets, diversify revenue streams.

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.

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.

Autonomous driving represents the ultimate goal of future automobile development. As a collaborative application that integrates vehicles, road infrastructure, network and cloud, autonomous driving business requires a high-degree dynamic cooperation among multiple resources such as data, computing and communications that are distributed throughout the system. In order to meet the anticipated high demand for resources and performance requirements of autonomous driving, and to ensure the safety and comfort of the vehicle users and pedestrians, a top concern of autonomous driving is to understand the system requirements for resources and conduct an in-depth analysis of the autonomous driving business. In this context, this paper presents a comprehensive analysis of the typical business for autonomous driving and establishes an analysis model for five common capabilities, i.e. collection, transmission, intelligent computing, human-machine interaction (HMI), and security.

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.

This document applies to the development of Plans for integrating and managing COTS assemblies in electronic equipment and Systems for the commercial, military, and space markets; as well as other ADHP markets that wish to use this document. For purposes of this document, COTS assemblies are viewed as electronic assemblies such as printed wiring assemblies, relays, disk drives, LCD matrices, VME circuit cards, servers, printers, laptop computers, etc. There are many ways to categorize COTS assemblies1, including the following spectrum: At one end of the spectrum are COTS assemblies whose design, internal parts2, materials, configuration control, traceability, reliability, and qualification methods are at least partially controlled, or influenced, by ADHP customers (either individually or collectively). An example at this end of the spectrum is a VME circuit card assembly.

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.