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Its extensive application of data networks, including enhanced external digital communication, forced the Federal Aviation Administration (FAA), for the first time, to set “Special Conditions” for cybersecurity. In the 15 years that ensued, airworthiness regulation followed suit, and all key rule-, regulation-, and standard-making organizations weighed in to establish a new airworthiness cybersecurity superset of legislation, regulation, and standardization. ...In the 15 years that ensued, airworthiness regulation followed suit, and all key rule-, regulation-, and standard-making organizations weighed in to establish a new airworthiness cybersecurity superset of legislation, regulation, and standardization. The resulting International Civil Aviation Organization (ICAO) resolutions, US and European Union (EU) legislations, FAA and European Aviation Safety Agency (EASA) regulations, and the DO-326/ED-202 set of standards are already the de-facto, and soon becoming the official, standards for legislation, regulation, and best practices, with the FAA already mandating it to a constantly growing extent for a few years now—and EASA adopting the set in its entirety in July 2020.

Automotive electronics and enterprise IT are converging and thus open the doors for advanced hacking. With their immediate safety impact, cyberattacks on such systems will endanger passengers. Today, there are various methods of security verification and validation in the automotive industry. However, we realize that vulnerability detection is incomplete and inefficient with classic security testing. In this article, we show how an enhanced Grey-Box Penetration Test (GBPT) needs less test cases while being more effective in terms of coverage and indicating less false positives.

To build secure systems of road vehicles, the cybersecurity engineering standard ISO21434[11] suggests the evaluation of vulnerabilities throughout engineering process, such as attack path analysis, system requirement stage, software architecture, design, and implementation and testing phases. ...With my analysis and practices, it is appropriate to include the common vulnerabilities that ought to be an integral part of the automotive cybersecurity engineering process. In this paper, the author would like to provide a list of vulnerabilities that might be a suggestion for threat analysis and risk assessment and propose two solutions that may be adopted directly in the V-model for security-relevant software development.

Symbolic code execution is a powerful cybersecurity testing approach that facilitates the systematic exploration of all paths within a program to uncover previously unknown cybersecurity vulnerabilities. ...Symbolic code execution is a powerful cybersecurity testing approach that facilitates the systematic exploration of all paths within a program to uncover previously unknown cybersecurity vulnerabilities. This is achieved through a Satisfiability Modulo Theory (SMT) solver, which operates on symbolic values for program inputs instead of using their concrete counterparts.

We also analyze how useful Cybersecurity Assurance Levels (CAL) are in this process and how quantitative as well as qualitative metrics can be utilized as evidence.

Additional complicating factors, such as cybersecurity concerns combined with a first responder’s legal authority, may pose challenges for traditional data collection.

As a promising strategic industry group that is rapidly evolving around the world, autonomous vehicle is entering a critical phase of commercialization from demonstration to end markets. The global automotive industry and governments are facing new common topics and challenges brought by autonomous vehicle, such as how to test, assess, and administrate the autonomous vehicle to ensure their safe running in real traffic situations and proper interactions with other road users. Starting from the facts that the way to autonomous driving is the process of a robot or a machine taking over driving tasks from a human. This paper summarizes the main characteristics of autonomous vehicle which are different from traditional one, then demonstrates the limitations of the existing certification mechanism and related testing methods when applied to autonomous vehicle.

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.

This paper will provide an Overview of Automotive Cyber Security Standards related to the Vehicle OBD-II Data Link. The OBD-II Connector Attack Tree is described with respect to the SAE J3138 requirements for Intrusive vs. non-Intrusive Services. A proposed test method for SAE J3138 is described including hardware and software scripting. Finally, example test results are reviewed and compared with a potential threat boundary.

Modern automobiles collect around 25 gigabytes of data per hour and autonomous vehicles are expected to generate more than 100 times that number. In comparison, the Apollo Guidance Computer assisting in the moon launches had only a 32-kilobtye hard disk. Without question, the breadth of in-vehicle data has opened new possibilities and challenges. The potential for accessing this data has led many entrepreneurs to claim that data is more valuable than even the vehicle itself. These intrepid data-miners seek to explore business opportunities in predictive maintenance, pay-as-you-drive features, and infrastructure services. Yet, the use of data comes with inherent challenges: accessibility, ownership, security, and privacy. Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles examines some of the pressing questions on the minds of both industry and consumers. Who owns the data and how can it be used?

Advanced Autonomous Vehicles (AV) for SAE Level 3 and Level 4 functions will lead to a new understanding of the operation phase in the overall product lifecycle. Regulations such as the EU Implementing Act and the German L4 Act (AFGBV) request a continuous field surveillance, the handling of critical E/E faults and software updates during operation. This is required to enhance the Operational Design Domain (ODD) during operation, offering Functions on Demand (FoD), by increasing software features within these autonomous vehicle systems over the entire digital product lifecycle, and to avoid and reduce downtime by a malfunction of the Autonomous Driving (AD) software stack.