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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CITATION STYLE
Huang, B., Mo, J., & Cheng, X. (2018). Improving security and stability of AODV with fuzzy neural network in VANET. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10874 LNCS, pp. 177–188). Springer Verlag. https://doi.org/10.1007/978-3-319-94268-1_15
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