Secure Vehicle-to-Vehicle Communication Using Routing Protocol Based On Trust Authentication Secure Sugeno Fuzzy Inference System Scheme

Abstract

Introduction: Vehicular Ad-hoc Network (VANET) is wireless communication between Roadside vehicles and vehicle infrastructure. Vehicle Ad Hoc Network (VANET) is a promising technology that effectively manages traffic and ensures road safety. However, communication in an open-access environment presents real challenges to security and privacy issues, which may affect large-scale deployments of VANETs. Vehicle identification, classification, distribution rates, and communication are the most challenging areas in previous methods. Vehicular communications face challenges due to vehicle interference and severe delays. Method: To overcome the drawbacks, this work proposed a new method based on the Artificial Neural Network Trust Authentication Secure Sugeno Fuzzy System (AN2-TAS2FS). Vehicular Ad Hoc Networks (VANET) are required to transmit data between vehicles and use traffic safety indicators. Improved Cluster-Based Secure Routing Protocol (ICSRP). Artificial Neural Network Based Trust Authentication Secure Sugeno Fuzzy System (AN2-TAS2FS) used the symmetric key to increase the security performance of VANET. Use ANFIS-based Secure Sugeno Fuzzy System for calculating the node weights for data transferring; reduced the attacks accuracy of network malicious attacks. objective: To overcome the drawbacks, this work proposed a new method based on Artificial Neural Network Based Trust Authentication Secure Sugeno Fuzzy System (AN2-TAS2FS). Vehicular Ad Hoc Networks (VANET) are required to transmit data between vehicles and use traffic safety indicators Improved Cluster-Based Secure Routing Protocol (ICSRP). Artificial Neural Network Based Trust Authentication Secure Sugeno Fuzzy System (AN2-TAS2FS) used the symmetric key to increase the security performance of VANET. Result: In the improved cluster-based VANET routing protocol, each node obtains an address using a new addressing scheme between the wireless vehicle-2-vehicle (V2V) exchanges and the Roadside Units (RSUs). It will explore the effectiveness of the Secure Sugeno Fuzzy System-based adaptation term Enhanced Cluster-based routing protocol in finding the vehicle's shortest-path for transmission. Conclusion: Simulation results show that in the proposed ANN-based Trust Authentication Secure Sugeno Fuzzy System (AN2-TAS2FS) analysis, the packet delivery ratio is 93%, delay performance is 0.55sec, throughput performance is 94%, bandwidth is 55bits/sec, Network security is 92%, and the transmission ratio is 89%, attack detection is 90%.