<p>Vehicular Adhoc Networks (VANETs) are assumed as the key phase for instant vehicle communication and offer secure road data. This network is utilized to transmit information among the vehicles by distributing the message to the vehicles. Due to selfishness and malicious behavior, the malicious nodes spread false secure alerts on the system. The fake news on the VANET modifies the behavior of the driver and fabricates a harmful condition on the system. Hence, it is essential to neglect these false messages on the system. Although the communication channel has an open wireless nature, VANETs are more sensitive to the security attacks created by malicious users. Moreover, the fake messages and the nodes can highly compromise the efficiency and the safety of the vehicle communication systems, resulting in disruptions in traffic flow and potential accidents. To overcome this issue, it is necessary to create a secure anonymous authentication approach for the VANET. If a vehicle arrives at the latest Road Side Units (RSU) exposure area, it must implement the authentication procedure along with the latest RSU that considerably minimizes the effectiveness of the whole VANET network. Authentication of vehicles, privacy preservation, and integrity of the transferred message are the necessary aspects of the security of VANET. Several VANET security solutions don’t meet the efficiency and security needs. Therefore, a secured protocol for fake news detection and optimal routing in VANET is implemented in this paper. Initially, the authentication of the vehicle nodes is detected utilizing the Adaptive Residual Long Short Term Memory (ARLSTM) model. This authentication process improves security and eliminates the unauthorized access. Moreover, the authenticated nodes can distribute accurate information, thus balancing the traffic flow and minimizing congestion. Additionally, the performance offered by this model is improved with the utilization of the Improved COOT Optimization Algorithm (ICOA). This designed algorithm optimally determines the parameters of the RLSTM model thereby increasing the effectiveness of the authentication operation. Once the authentication of the form is verified, then the nodes are allowed to transmit the messages to another vehicle. However, there still exists a possibility of evading an authenticated user node and generating false messages. Therefore, to prevent false messages from being transmitted, a fake news detection scheme is implemented in this work with the aid of the Beacon Trust Management System and Fake Data Detection. This model relatively prevents the propagation of fake news thus minimizing the risk of confusion and dangerous threats. Additionally, this model increases safety and efficiency. Once the fake news is detected, they are eliminated from the system. Efficient communication is carried out by utilizing an optimal routing protocol. The optimal routing is performed with the aid of the same ICOA by focussing the multi-objective constraints such as trust, delay, and Packet Delivery Ratio. The ICOA-aided optimal routing process increases the network performance and minimizes network congestion. Also, this process improves the reliability and minimizes the packet loss. The experimental examination is completed to prove the effectiveness of the implementation scheme. From the experimental validation, it has been observed that the implemented ARLSTM-based node authentication model achieved 93% accuracy, which is greater than the traditional authentication models including MHT (90.2%), ACO (91.9%), Fuzzy (92.4%), and EGSR (90.7%). Thus, the experiments ensured that the designed model efficiently performs the fake news identification by performing node authentication and optimal routing thus increasing the security of the VANET.</p>