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A survey of trust management systems for online social communities - Trust modeling, trust inference and attacks

机译:在线社交社区信任管理系统的调查-信任建模,信任推断和攻击

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摘要

Trust can help participants in online social communities to make decisions; however, it is a challenge for systems to map trust into computational models because of its subjective properties. Also, many online social communities are sparsely connected. Therefore, it is necessary to introduce mechanisms which can infer indirect trust among participants who are not directly connected. We provide a survey of existing trust management systems for online social communities. We also list four types of attacks, and analyze existing systems' vulnerabilities. Compared with previous surveys, our survey takes trust modeling, trust inference, and attacks into account. Although there are several survey papers about global trust/reputation related attacks, the main contribution of this paper is that we consider trust inference and potential local trust related attacks. (C) 2016 Elsevier B.V. All rights reserved.
机译:信任可以帮助在线社交社区的参与者做出决策;但是,由于系统具有主观性,因此将信任映射到计算模型是一个挑战。此外,许多在线社交社区之间的联系稀疏。因此,有必要引入一种机制,以推断未直接连接的参与者之间的间接信任。我们提供了有关在线社交社区的现有信任管理系统的调查。我们还列出了四种攻击类型,并分析了现有系统的漏洞。与以前的调查相比,我们的调查考虑了信任建模,信任推断和攻击。尽管有几篇有关全局信任/信誉相关攻击的调查论文,但本文的主要贡献是我们考虑了信任推断和潜在的本地信任相关攻击。 (C)2016 Elsevier B.V.保留所有权利。

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