This chapter delves into the fusion of cutting-edge machine learning (ML) and deep learning (DL) technologies within cloud-powered smart security systems, specifically designed for vehicular mobile crowdsensing (MCS) environments. By integrating ML and DL capabilities, these advanced systems transcend traditional security measures, empowering real-time threat detection and response mechanisms. We explore how these sophisticated technologies effectively address the dynamic nature of contemporary cyber threats, ensuring the integrity and reliability of MCS data streams. Furthermore, a detailed case study is presented, highlighting the implementation and efficacy of a cloud-powered defense strategy against phishing attacks within the Internet of Vehicles (IoV). Through this case study, we showcase the accuracy, efficiency, and transformative potential of AI-driven security solutions in fortifying digital ecosystems against evolving threats.