A trust model based on fuzzy recommendation for mobile ad-hoc networks

Abstract

In a mobile ad-hoc network (MANET) environment, intermediate nodes on a communication path are expected to forward packets of other nodes so that the mobile nodes can communicate beyond their wireless transmission range. However, because mobile nodes are usually constrained by limited energy, bandwidth and computational power, a selfish node may be unwilling to spend its resources in forwarding packets which are not of its direct interest, even though it expects other nodes to forward its packets to the destination. Selfish behavior of autonomous network nodes could greatly disrupt network operation and degrade the overall performance of a non-cooperative ad-hoc network. Nodes have to manage the risk involved with the transactions without prior knowledge about each other's reputation. Currently, some methods for trust establishment in MANETs have been proposed based on using cryptographic primitives to address cooperation among nodes attributes and handle selfish behaviors of nodes in MANETs environment. However, these solutions are not always suited to MANETs. The measurement and computation of trust to secure interactions between mobile nodes is crucial for the development of trust mechanisms. The calculation and measurement of trust in unsupervised ad-hoc environment involves complex aspects such as credibility rating for opinions delivered by a node, the honesty of recommendations provided by a mobile node, or the assessment of past experiences with the node one wishes to interact with. The deployment of suitable algorithms and models imitating fuzzy logic can help to solve these problems. In this paper, RFSTrust, a trust model based on fuzzy recommendation similarity, is proposed to quantify and to evaluate the trustworthiness of nodes, which includes five types of fuzzy trust recommendation relationships based on the fuzzy relation theory and a mathematical description for MANETs. Fuzzy logic provides a natural framework to deal with uncertainty and the tolerance of imprecise data inputs for the subjective tasks of trust evaluation, packet forwarding review and credibility adjustment. Theoretical analysis and experimental results show that RFSTrust is still robust under more general conditions where selfish nodes cooperate in an attempt to deliberately subvert the system, end-to-end packet delivery ratio more quickly, and decreases the average energy consumes more effectively. The effect of node rating data's sparsity can be greatly reduced and show the excellent performance on typical data set.