Search Results

The recently released SAE J3061 guidebook for cyber-physical vehicle systems provides high-level principles for automotive organizations for identifying and assessing cybersecurity threats and for designing cybersecurity aware systems in close relation to the ISO 26262 standard for the functional safety of road vehicles. ...., infotainment, car-2-car or car-2-infrastructure communication) as well as new advances toward advanced driver assistance systems (ADAS) or even autonomous driving functions make cybersecurity another key factor to be taken into account by vehicle suppliers and manufacturers. ...Although these can capitalize on experiences from many other domains, they still have to face several unique challenges when gearing up for specific cybersecurity challenges. A key challenge is related to the increasing interconnection of automotive systems with networks (such as Car2X).

The article also focus on innovative approaches that have recently adopted my many cybersecurity professionals for secured operation of ITS involving block-chain, artificial intelligence, and Machine Learning.

Also, all the existing methods for vehicular communication rely on a centralized server which itself invite massive cyber-security threats. These threats and challenges can be addressed by using the Blockchain (BC) technology, where each transaction is logged in a decentralized immutable BC ledger.

With the introduction of Connected Vehicles, it is possible to extend the limited horizon of vehicles on the road by collective perceptions, where vehicles periodically share their information with other vehicles and servers using cloud. Nevertheless, by the time the connected vehicle spread expands, it is critical to understand the validation techniques which can be used to ensure a flawless transfer of data and connectivity. Connected vehicles are mainly characterized by the smartphone application which is provided to the end customers to access the connectivity features in the vehicle. The end result which is delivered to the customer is through the integrated telematics unit in the vehicle which communicates through a communication layer with the cloud platform. The cloud server in turn interacts with the final application layer of the mobile application given to the customer.

The ever-increasing complexity and connectivity of driver assist functions pose challenges for both Functional Safety and Cyber Security. Several of these challenges arise not only due to the new functionalities themselves but due to numerous interdependencies between safety and security. Safety and security goals can conflict, safety mechanisms might be intentionally triggered by attackers to impact functionality negatively, or mechanisms can compete for limited resources like processing power or memory to name just some conflict potentials. But there is also the potential for synergies, both in the implementation as well as during the development. For example, both disciplines require mechanisms to check data integrity, are concerned with freedom from interference and require architecture based analyses. So far there is no consensus in the industry on how to best deal with these interdependencies in automotive development projects.

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.

Software vulnerability management is one of the most critical and crucial security techniques, which analyzes the automotive software/firmware across the digital cockpit, ADAS, V2X, etc. domains for vulnerabilities, and provides security patches for the concerned Common Vulnerabilities and Exposures (CVE). The process of automotive SW/FW vulnerability management system between the OEMs and vendors happen through a channel of fixing a certain number of vulnerabilities by 1st tier supplier which needs to be verified in front of OEMs for the fixed number and type of patches in there deliverable SW/FW. The gap of verification between for the fixed patches between the OEMs and 1st tier supplier requires a reliable human independent intelligent technique to have a trustworthiness of verification.

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.

It is deemed that currently the intelligent connected vehicle (ICV) is in its early stage of development, and it will go through multiple development stages in the future to realize its final goal—autonomous driving. Based on the existing ICV researches, this paper believes that ICV can be used to improve the efficiency and safety of freeway. The current research of ICV has two main directions: one focuses on the traffic flow characteristics of vehicles with different attributes, the other is concerned with using ICV to reduce congestion. From the policies issued by countries around the world and the development plans promoted by major vehicle manufacturers, the future development trends and challenges of ICV are analyzed. ICV must overcome all the shortcomings to achieve its final goal, including insufficient hardware capabilities or excessive cost, and the degree of intelligence that needs to be improved.

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.