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A smartphone-based online social network trust evaluation system


Charles Perez, Babiga Birregah & Marc Lemercier


Social Network Analysis and Mining


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Keywords : Social networks; Trust; Mobile devices; Illegitimate contacts; Overlap; ML-modelnline Social networks; Trust; Mobile devices; Illegitimate contacts; Overlap; ML- model




The number of smartphone users has increased significantly over the last decade. The number of people using social networking sites is also increasing, and these platforms offer many features through which individuals can communicate with their contacts. The digital sphere is an opportunity for communication, but it is also an unprecedented arena for malicious attacks. The high quantity of personal and/or sensitive data, coupled with the large number of users, is one of the main motivations of malicious actors. We introduce in this paper a novel trust indicator for evaluating the contacts of an online social network user. This analysis is particularly important since the security policy of online social networks rests on the principle that a user’s contact is a person of trust. This assumption, not always verified as true, gives any number of people access to personal information. To address this problem, we propose applying a multi-layer model and extend it by proposing overlapping features that highlight the level of overlap of a contact belonging to the set of social networking friends of a smartphone user. We prove the efficiency of these features in evaluating trust using a case study with Facebook and Twitter.

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