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Bounding Trust under Uncertain Topology Information in Reputation-Based Trust Systems

机译:基于信誉的信任系统中不确定拓扑信息下的边界信任

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Reputation-based trust evaluation relies on the feedback of an entity's past interactions to estimate its trustworthiness for future behavior. Past work commonly assumes that all the information needed in trust evaluation is always available, which, unfortunately, often does not hold in practice, due to a variety of reasons. A key problem is thus to study the quality of trust evaluation in the presence of incomplete information. In this paper, we investigate techniques to bound the output of a trust evaluation under uncertain graph topologies of a reputation system. We present a rigorous formalism of the problem, and establish connections between uncertain topology information and missing feedback information through a property called edge reducibility. We show that the trust bounding problem can be efficiently solved if a trust function is edge reducible.
机译:基于信誉的信任评估依赖于实体过去交互的反馈来估计其对未来行为的信任度。过去的工作通常假定信任评估所需的所有信息都是始终可用的,但不幸的是,由于种种原因,这些信息通常在实践中并不适用。因此,关键问题是在信息不完整的情况下研究信任评估的质量。在本文中,我们研究了在信誉系统的不确定图拓扑下绑定信任评估输出的技术。我们提出了严格的问题形式化方法,并通过称为边可约性的属性在不确定的拓扑信息和缺失的反馈信息之间建立了联系。我们表明,如果信任函数是边缘可约的,则可以有效地解决信任边界问题。

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