The Internet of Vehicles (IoV) establishes a comprehensive network that connects vehicles, pedestrians, and urban infrastructure elements. In the IoV paradigm, vehicles function as intelligent entities equipped with sensing platforms and computing facilities, facilitating connectivity with other vehicles, roadside units (RSUs), and cloud servers. The advancements in autonomous driving present challenges, with a primary emphasis on addressing security threats associated with the sharing of data among various IoV entities. Within the realm of IoV, a thorough analysis of the substantial big data generated by vehicles is imperative for making informed decisions and inferences. This paper proposes a secure framework for big data analytics (BDA), wherein the data collected from vehicles undergoes a secure analysis at the BDA center. The effectiveness of the proposed methodology is showcased through a comprehensive analysis of security, resilience against attacks, and big data analytics performance.