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Improving Security and Stability of AODV with Fuzzy Neural Network in VANET

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Wireless Algorithms, Systems, and Applications (WASA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10874))

Abstract

To improve security and stability of AODV in VANET (Vehicle Ad hoc Network), a secure and stable AODV, named GSS-AODV is proposed. GSS-AODV uses a fuzzy neural network to compute the node information in routing activities. The stability of nodes is computed to evaluate links. The link stability and the number of hops are considered in a balanced way, so a stable path with fewer hops is selected. GSS-AODV uses trust value of the node to evaluate the node security. The evaluation balances node security with network environment and node utilization to prevent malicious node attack. In routing maintenance, GSS-AODV uses genetic simulated annealing algorithm to optimize the parameters of the fuzzy neural network in real time to ensure that the calculated stability and trust value of node match the actual situation.

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Acknowledgements

This work was supported by National Natural Science Foundation of China under Grant No. 61262072.

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Authors and Affiliations

  1. School of Computer and Electronic Information, Guangxi University, Nanning, 530004, Guangxi, China

    Baohua Huang & Jiawei Mo

  2. Department of Computer Science, Virginia Commonwealth University, Richmond, VA, 23220, USA

    Xiaolu Cheng

Authors
  1. Baohua Huang
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  2. Jiawei Mo
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  3. Xiaolu Cheng
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Corresponding author

Correspondence to Baohua Huang .

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Editors and Affiliations

  1. University of South Florida, Tampa, Florida, USA

    Sriram Chellappan

  2. Virginia Commonwealth University, Richmond, Virginia, USA

    Wei Cheng

  3. Georgia State University, Atlanta, Georgia, USA

    Wei Li

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Huang, B., Mo, J., Cheng, X. (2018). Improving Security and Stability of AODV with Fuzzy Neural Network in VANET. In: Chellappan, S., Cheng, W., Li, W. (eds) Wireless Algorithms, Systems, and Applications. WASA 2018. Lecture Notes in Computer Science(), vol 10874. Springer, Cham. https://doi.org/10.1007/978-3-319-94268-1_15

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  • DOI: https://doi.org/10.1007/978-3-319-94268-1_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94267-4

  • Online ISBN: 978-3-319-94268-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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