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With the increasing connectivity and complexity of modern automobiles, cybersecurity has become one of the most important properties of a vehicle. Various strategies have been proposed to enhance automotive cybersecurity. ...Various strategies have been proposed to enhance automotive cybersecurity. Digital twin (DT), regarded as one of the top 10 strategic technology trends by Gartner in 2018 and 2019, establishes digital representations in a virtual world and raises new ideas to benefit real-life objects. ...In this paper, we explored the possibility of using digital twin technology to improve automotive cybersecurity. We designed two kinds of digital twin models, named mirror DT and autonomous DT, and corresponding environments to support cybersecurity design, development, and maintenance in an auto’s lifecycle, as well as technique training.

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.

Due to the rapid development in the technological aspect of the autonomous vehicle (AV), there is a compelling need for research in the field vehicle efficiency and emission reduction without affecting the performance, safety and reliability of the vehicle. Electric vehicle (EV) with rechargeable battery has been proved to be a practical solution for the above problem. In order to utilize the maximum capacity of the battery, a proper power management and control mechanism need to be developed such that it does not affect the performance, reliability and safety of vehicle. Different optimization techniques along with deterministic dynamic programming (DDP) approach are used for the power distribution and management control. The battery-operated electric vehicle can be recharged either by plug-in a wired connection or by the inductive mean (i.e. wirelessly) with the help of the electromagnetic field energy.

Since the early 1990’s, commercial vehicles have suffered from repeated vulnerability exploitations that resulted in a need for improved automotive cybersecurity. This paper outlines the strategies and challenges of implementing an automotive Zero Trust Architecture (ZTA) to secure intra-vehicle networks. ...This research successfully met the four requirements and demonstrated that using ZT principles in an on-vehicle network greatly improved the cybersecurity posture with manageable impact to system performance and deployment.

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.

The caveat to these additional capabilities is issues like cybersecurity, complexity, etc. This paper is an exploration into FuSa and CAVs and will present a systematic approach to understand challenges and propose potential framework, Intelligent Vehicle Monitoring for Safety and Security (IVMSS) to handle faults/malfunctions in CAVs, and specifically autonomous systems.

As an important part of intelligent driving vehicles and intelligent networked transportation systems, environmental perception technology can provide important decision-making basis for the overall planning of intelligent driving vehicles and transportation systems. This paper reviews the current research on environment perception technology in the current intelligent networked transportation system, and analyzes four key research directions and related progress of environmental sensing technologies, including single sensor device, high-precision map, multi-sensor information fusion and vehicle-road collaboration. On the basis of analyzing and summarizing existing related research, this article elaborates the development trend and key directions of future environmental perception technology, including the integration of deep learning, vehicle-road integration, information security and multi-dimensional perception technology related development directions.

Upon their arrival, Unmanned Autonomous Systems (UAS) brought with them many benefits for those involved in a military campaign. They can use such systems to reconnoiter dangerous areas, provide 24-hr aerial security surveillance for force protection purposes or even attack enemy targets all the while avoiding friendly human losses in the process. Unfortunately, these platforms also carry the inherent risk of being built on innately vulnerable cybernetic systems. From software which can be tampered with to either steal data, damage or even outright steal the aircraft, to the data networks used for communications which can be jammed or even eavesdropped on to gain access to sensible information. All this has the potential to turn the benefits of UAS into liabilities and although the last decade has seen great advances in the development of protection and countermeasures against the described threats and beyond the risk still endures.

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.