In this paper, we propose a simple randomized protocol for identifyingtrusted nodes based on personalized trust in large scale distributed networks.The problem of identifying trusted nodes, based on personalized trust, in alarge network setting stems from the huge computation and message overheadinvolved in exhaustively calculating and propagating the trust estimates by theremote nodes. However, in any practical scenario, nodes generally communicatewith a small subset of nodes and thus exhaustively estimating the trust of allthe nodes can lead to huge resource consumption. In contrast, our mechanism canbe tuned to locate a desired subset of trusted nodes, based on the allowableoverhead, with respect to a particular user. The mechanism is based on a simpleexchange of random walk messages and nodes counting the number of times theyare being hit by random walkers of nodes in their neighborhood. Simulationresults to analyze the effectiveness of the algorithm show that using theproposed algorithm, nodes identify the top trusted nodes in the network with avery high probability by exploring only around 45% of the total nodes, and inturn generates nearly 90% less overhead as compared to an exhaustive trustestimation mechanism, named TrustWebRank. Finally, we provide a measure of theglobal trustworthiness of a node; simulation results indicate that the measuresgenerated using our mechanism differ by only around 0.6% as compared toTrustWebRank.
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