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Trust Assessment in Online Social Networks

机译:在线社交网络中的信任评估

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Assessing trust in online social networks (OSNs) is critical for many applications such as online marketing and network security. It is a challenging problem, however, due to the difficulties of handling complex social network topologies and conducting accurate assessment in these topologies. To address these challenges, we model trust by proposing the three-valued subjective logic (3VSL) model. 3VSL properly models the uncertainties that exist in trust, thus is able to compute trust in arbitrary graphs. We theoretically prove the capability of 3VSL based on the Dirichlet-Categorical (DC) distribution and its correctness in arbitrary OSN topologies. Based on the 3VSL model, we further design the AssessTrust (AT) algorithm to accurately compute the trust between any two users connected in an OSN. We validate 3VSL against two real-world OSN datasets: Advogato and Pretty Good Privacy (PGP). Experimental results indicate that 3VSL can accurately model the trust between any pair of indirectly connected users in the Advogato and PGP.
机译:评估在线社交网络(OSNS)的信任对于许多在线营销和网络安全等许多应用至关重要。然而,由于处理复杂的社交网络拓扑困难并对这些拓扑进行准确评估,这是一个具有挑战性的问题。为了解决这些挑战,我们通过提出三价主观逻辑(3VSL)模型来模拟信任。 3VSL适当地模拟信任中存在的不确定性,从而能够计算任意图形的信任。理论上,基于Dirichlet分类(DC)分布和其在任意OSN拓扑中的正确性,理论上理论上证明了3VSL的能力。基于3VSL模型,我们进一步设计了评估的算法,以准确地计算在OSN中连接的任何两个用户之间的信任。我们对两个现实世界OSN数据集进行验证3VSL:Advogato和非常良好的隐私(PGP)。实验结果表明,3VSL可以准确地模拟Advogato和PGP中的任何一对间接连接的用户之间的信任。

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