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., driver assistance functions, intrusion detection system, vehicle diagnostics, external device authentication during vehicle diagnostics, vehicle-to-grid and so on). The cybersecurity attacks targeting the global time result in false time, accuracy degradation, and denial of service as stated in IETF RFC 7384.

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.

Using a wireless medium for tractor-trailer communication will bring new cybersecurity challenges and requirements which requires new development and lifecycle considerations.

By looking into the vehicle-infrastructure cooperation (VIC) which is oriented towards intelligent, networked and integrated development, this paper analyzes and proposes the essence and development direction of Intelligent Vehicle Infrastructure Cooperation Systems (I-VICS). With an in-depth analysis of technologies of core importance to VIC and influence factors that constrain VIC development as a whole, the paper comes up with a technological route for VIC, and identifies a direction for vehicle-infrastructure cooperative development that progresses from primary to intermediate cooperation, then to advanced cooperation, and finally to full-fledged cooperation. Policy recommendations aiming at strengthening top-level design, building an integrated vehicle-infrastructure-cloud platform, expediting independence of key techs, building robust standards and regulations for VIC, enhancing workforce development as well as greater efforts at market promotion are put forward.

Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.

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.

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.

Unmanned ground vehicles (UGVs) may encounter difficulties accommodating environmental uncertainties and system degradations during harsh conditions. However, human experience and onboard intelligence can may help mitigate such cases. Unfortunately, human operators have cognition limits when directly supervising multiple UGVs. Ideally, an automated decision aid can be designed that empowers the human operator to supervise the UGVs. In this paper, we consider a connected UGV platoon under cyber attacks that may disrupt safety and degrade performance. An observer-based resilient control strategy is designed to mitigate the effects of vehicle-to-vehicle (V2V) cyber attacks. In addition, each UGV generates both internal and external evaluations based on the platoons performance metrics. A cloud-based trust-based information management system collects these evaluations to detect abnormal UGV platoon behaviors.