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

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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.

论文关键词:Online trust,Trust management,Online social communities,Attack

论文评审过程:Received 14 September 2015, Revised 19 May 2016, Accepted 21 May 2016, Available online 25 May 2016, Version of Record 18 June 2016.

论文官网地址:https://doi.org/10.1016/j.knosys.2016.05.042