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This talk will
cover Li’s recent works on the uncertainty-aware reputation system and the
analysis and applications based on the uncertainty-aware reputation system in
mobile networks. Evaluating and quantifying trust stimulates collaboration in
mobile networks. Many existing reputation systems sharply divide the trust
value into right or wrong, thus ignore another core dimension of trust
uncertainty. As uncertainty deeply impacts a node’s anticipation of others’
behavior and decisions during interaction, we include uncertainty in the
reputation system. Specifically, we use an uncertainty metric to directly
reflect a node’s confidence in the sufficiency of its past experience, and
study how the collection of trust information may affect uncertainty in nodes’
opinions. Higher uncertainty leads to higher transaction cost and reduced
acceptance of communication and cooperation. After defining a way to reveal and
compute the uncertainty in trust opinions, we exploit mobility, one of the
important characteristics of MANETs, to efficiently reduce uncertainty and to
speed up trust convergence.
In this talk, Li will also describe how to enhance traditional theories in the analysis of the interactions between mobile nodes by integrating uncertainty, and present three sample uncertainty-aware applications which show the broader impact of this new dimension of trust on the mobile networks.