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Sunday, 3 June 2018

A Privacy-Preserving Framework for Managing Mobile Ad Requests and Billing Information

The distinctive features of mobile ad hoc networks (MANETs), including dynamic topology and open wireless medium, may lead MANETs suffering from many security vulnerabilities. In this paper, using recent advances
in uncertain reasoning originated from artificial intelligence community, we propose a unified trust management scheme that enhances the security in MANETs. In the proposed trust management scheme, the trust model has two components: trust from direct observation and trust from indirect observation. With direct observation from an observer node, the trust value is derived using Bayesian inference, which is a type of uncertain reasoning when the full probability model can be defined. On the other hand, with indirect observation, also called secondhand information that is obtained from neighbor nodes of the observer node, the trust value is derived using the Dempster-Shafer theory, which is another type of uncertain reasoning when the proposition of interest can be derived by an indirect method. Combining these two components in the trust model, we can obtain more accurate trust values of the observed nodes in MANETs. We then evaluate our scheme under the scenario of MANET routing. Extensive simulation results show the effectiveness of the proposed scheme. Specifically, throughput and packet delivery ratio can be improved significantly with slightly increased average endto- end delay and overhead of messages

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