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Volume 19, Issue 1
  • ISSN: 1872-2121
  • E-ISSN: 2212-4047

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.

Methods

To overcome the drawbacks, this patent 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.

Results

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 0.55 sec, throughput performance is 94%, bandwidth is 55 bits/sec, Network security is 92%, and the transmission ratio is 89%, attack detection is 90%.

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2024-02-23
2025-02-17

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/content/journals/eng/10.2174/0118722121269253240214075231
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Secure Vehicle-to-Vehicle Communication using Routing Protocol based on Trust Authentication Secure Sugeno Fuzzy Inference System Scheme
Recent Pat Eng 19, E230224227390 (2025); https://doi.org/10.2174/0118722121269253240214075231
/content/journals/eng/10.2174/0118722121269253240214075231
/content/journals/eng/10.2174/0118722121269253240214075231
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  • Article Type:     Research Article
Keyword(s): Artificial Neural Network; cluster; Fuzzy; network; node; Roadside Units (RSUs); routing protocol; Trust Authentication; Vehicular Ad Hoc Networks (VANET)

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