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The ever-increasing demands of vehicular networkspose significant challenges such as availability, computation complexity, security, trust, authentication, etc. This becomes even morecomplicated for high-speed moving vehicles. As a result, increasing the capacity of these networks has been attracting considerableawareness. In this regard, the next generation of cellular networks,5G, is expected to be a promising solution enabling high data rates,capacity, and quality of service as well as low latency communications. However, 5G networks still face challenges in providingubiquitous and reliable connections among high-speed vehicles.Thus, to overcome the gaps in the existing solutions, we proposea software defined network (SDN)-based consolidated frameworkproviding end-to-end security and privacy in 5G enabled vehicularnetworks. The framework simplifies network management throughSDN, while achieving optimized network communications. It operates in two phases: first, an elliptic curve cryptographic basedauthentication protocol is proposed to mutually authenticate thecluster heads and certificate authority in SDN-based vehicular setups, and, second, an intrusion detection module supported by tensor based dimensionality reduction is designed to reduce the computational complexity and identify the potential intrusions in thenetwork. In order to assess the performance of the proposed framework, an extensive evaluation is performed on three simulators;NS3, SUMO, and SPAN. To harness the potential benefits of the proposed model, the first module, is evaluated on the basis of securityfeatures, whereas the second module is evaluated, and comparedwith the existing state-of-the-art models, on the basis of detectionrate, false positive rate, accuracy, detection time, and communication overhead. The simulation results indicate the superiority ofthe proposed framework as compared to the existing models.