Self-observation and recommendation based trust model with defense scheme for wireless ad hoc network

Abstract

In this paper, a self-observation and recommendation based trust model with defense scheme to filter dishonest recommendations is proposed and analyzed to reduce the impact of false positive and false negative attacks in WANET. The Bayesian statistical approach is used to compute direct and indirect trust values. The confidence value assures the maturity of the interactive relationship between the trust evaluating node and the evaluated node. The defense scheme filters the received recommendations by comparing them with the node’s own opinion and in case of no interaction with the evaluated node, it compares with a trusted neighbor’s opinion. The neighbor nodes are tagged into three categories: Trusted neighbor, untrusted neighbor and unknown neighbor according to the overall similarity score. The defense scheme only accepts the recommendations from trusted and unknown neighbors. The proposed trust model is simulated and the results show that the model is capable of mitigating the influence of badmouthing and ballot-stuffing attacks.

Keywords

Wireless Ad hoc Network Trust model Bayesian statistical approach Direct and indirect trust recommendation filtration

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