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Uncertainty is an unresolved problem in MANET, especially while evaluating the trust of the network.
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In this way, we can evaluate the trust of the vehicle node more accurately.
The basic idea is to build a trust model that provides a mechanism to evaluate the trust of its neighbors.
Hallani et al. [45] uses a fuzzy-based approach to evaluate the trust of a node and then decide the trustworthiness of a node.
CGTrust provides a mechanism to evaluate the trust of both non-CH nodes and CHs to prevent false trustworthiness decisions of non-CH nodes by a non-trustworthy CH and minimize the setup and reconfiguration time.
The solution we present here is based on public and symmetric key encryption and allows users seamless access, during a limited period of time fixed by the authentication system, to information provider Web servers through points of access that evaluate the trust of the user requests.
As shown in Fig. 3, the computational complexity is directly proportional to the computational time required in evaluating the trust profile of all nodes of the MANET.
The recommendations called evidences received from the cluster neighbours give assistance in evaluating the trust value of x.The DS theory is used in practice with uncertainty or ignorance to evaluate the value of trust.
In order to minimize the time required to evaluate the trust profile of a large MANET, the optimal cluster size (k optimal) that minimizes the computational complexity used in evaluating the trust profile of all nodes in the network is derived.
The recommendation based trust value calculation process, while evaluating the trust value given by the service, takes into account the sensitivity of the service interface offering the recommendation.
In the trust to authority dimension, two statements evaluated the trust to regulatory institutions and one statement asked for the opinion on regulations ('1' very high trust, '5' no trust; '1' absolutely agree; '5' no agreement).
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