ABSTRACT
An intelligent transportation system is regarded as one of the most indispensable constituents within the context of the smart cities in a bid to realize highly safe and efficacious traffic flows. It facilitates vehicles to communicate with numerous other road entities and the supporting infrastructure via vehicle-to-everything communication to guarantee both safety-critical and non-safety (i.e., infotainment) applications. Nevertheless, road entities in such sort of an IoV network are also prone to a number of internal and external attacks with the former one unable to be identified via the classical security, i.e., cryptographic-based, schemes. In Chapter 4, a scalable hybrid trust model has been envisaged which is capable of ensuring both the real-time identification and eradication of multiple malicious vehicles via employing a composite metric (i.e., encompassing the weighted amalgamation of a vehicle's computed trust score and its corresponding available resources) to guarantee that the stringent performance requirements of the safety-critical vehicular applications could be entirely met. Also, a Hungarian algorithm based optimal role assignment scheme has been envisaged in a bid to select an optimal cluster head, proxy cluster head, and followers among members of a vehicular cluster for maximizing its overall efficacy. Furthermore, the notion of an adaptive threshold has been put forward for identifying and subsequently eliminating the smart malicious vehicles from the network in a timely manner, i.e., as soon as they start exhibiting an adverse behavior, to ensure that the network could not be manipulated for any sort of malicious gains.
