Trust-aware FuzzyClus-Fuzzy NB: intrusion detection scheme based on fuzzy clustering and Bayesian rule.

The dynamic nature of the nodes on the mobile ad hoc network (MANET) imposes security issues in the network and most of the Intrusion detection methods concentrated on the energy dissipation and obtained better results, whereas the trust remained a hectic factor. This paper proposes a trust-aware scheme to detect the intrusion in the MANET. The proposed Trust-aware fuzzy clustering and fuzzy Naive Bayes (trust-aware FuzzyClus-Fuzzy NB) method of detecting the intrusion is found to be effective. The fuzzy clustering concept determines the cluster-head to form the clusters. The proposed BDE-based trust factors along with the direct trust, indirect trust, and the recent trust, hold the information of the nodes and the fuzzy Naive Bayes determine the intrusion in the nodes using the node trust table. The simulation results convey the effectiveness of the proposed method and the proposed method is analyzed based on the metrics, such as delay, energy, detection rate, and throughput. The delay is in minimum at a rate of 0.00434, with low energy dissipation of 9.933, high detection rate of 0.623, and greater throughput of 0.642. [ABSTRACT FROM AUTHOR]