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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.

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.

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.

Vehicles have more connectivity options now-a-days and these increasing connection options are giving more chances for an intruder to exploit the system. So, the vehicle manufacturers need to make the ECU in the vehicle more secure. To make the system secure, the embedded system must secure all the assets in the system. Examples of assets are Software, Kernel or Operating system, cryptographic Keys, Passwords, user data, etc. In this, securing the Kernel is extremely important as an intruder can even exploit the operating system characteristics just by changing the kernel code without introducing a trojan in the system. Also, the Kernel is the one entity that manages all permissions, so, if the kernel is hacked, these permissions also get compromised. The proposed approach is to make the kernel secure by doing the integrity check periodically of the kernel code loaded into the main memory of the system.

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?

There continues to be massive advancements in modern connected vehicles and with these advancements, connectivity continues to rapidly become more integral to the way these vehicles are designed and operated. Vehicle connectivity was originally introduced for the purpose of providing software updates to the vehicle’s main system software, and we have seen the adoption of Over The Air updates (OTA) become mainstream with most OEMs. The exploitation of this connectivity is far more reaching than just basic software updates. In the latest vehicles it is possible to update software not just on the main vehicle systems, but to potentially update embedded software in all smart ECUs within the vehicle. Only using the connectivity to push data to the vehicle is not making full use of the potential of this increased connectivity. Being able to collect vehicle data for offline analysis and processing also brings huge benefits to the use of this technology.

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.