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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.

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.

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.

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.

Their associated information technology and cyber physical systems—along with an exponentially resultant number of interconnections—present a massive cybersecurity challenge. Unlike the physical security challenge, which was treated in earnest throughout the last decades, cyber-attacks on airports keep coming, but most airport lack essential means to confront such cyber-attacks. ...These missing means are not technical tools, but rather holistic regulatory directives, technical and process standards, guides, and best practices for airports cybersecurity—even airport cybersecurity concepts and basic definitions are missing in certain cases. Unsettled Topics Concerning Airport Cybersecurity Standards and Regulation offers a deeper analysis of these issues and their causes, focusing on the unique characteristics of airports in general, specific cybersecurity challenges, missing definitions, and conceptual infrastructure for the standardization and regulation of airports cybersecurity. ...Unsettled Topics Concerning Airport Cybersecurity Standards and Regulation offers a deeper analysis of these issues and their causes, focusing on the unique characteristics of airports in general, specific cybersecurity challenges, missing definitions, and conceptual infrastructure for the standardization and regulation of airports cybersecurity.

Day by day, airports adopt more IoT devices. However, airports are not exempt from possible failures due to malware’s proliferation that can abuse vulnerabilities. Computer criminals can access, corrupt, and extract information from individuals or companies. This paper explains the development of a propagation model, which started with a Delphi process. We discuss the preliminary implications for airports of the simulation model built from the Delphi recommendations.