A Vehicular Ad hoc Network (VANET) is a recent innovation in information and communication technologies to allow communications among vehicles and enable a connected and autonomous transportation system. However, its security and resilience are of serious concern. This talk aims to give an overview of cybersecurity threats and models in transportation systems. We will present computational and analytical frameworks that have been developed to assess cyber risks of connected and autonomous vehicles (CAVs) and develop detection techniques based on learning algorithms. We integrate multi-modal connectivity as one of the primary resilience mechanisms to allow transportation networks to adapt and reconfigure to CAVs, evaluated as scenarios in the context of trip purposes and human attitudes toward the use of CAVs.