Abstract
Privacy risk in Online Social Networks has become an important social concern. Users, with different perceptions of risk, share information without considering the audience that has access to the information disclosed or how far a publication will go. According to this, we propose two metrics (Audience and Reachability) based on information flows and friendship layers that indicate the privacy risk of sharing information, addressing the posts' scope and invisible audience. We assess these metrics through agent simulations in well-known models of networks. The findings show a strong relationship between metrics and structural centrality network properties. We also studied scenarios where there is no previous information about users activity or the information about the traces of the messages cannot be obtained. To deal with privacy assessment in these scenarios, we analyze the relationship between the proposed privacy metrics and local centrality properties as an estimation of privacy risk. The results showed that effectiveness centrality can be used as a suitable approximation of the proposed privacy measures.
Highlights
One of the most common online activities in the European Union in 2014 was participation in social networking [13]
Regarding problems with privacy awareness and privacy settings configuration in Online Social Networks (OSNs), the provision of metrics and mechanisms that facilitate the management of individuals’ privacy and enhance the awareness of privacy risks become an important issue [39], The associate editor coordinating the review of this manuscript and approving it for publication was Haipeng Yao
In this paper, we have presented a new model of privacy risk based on friendship layers
Summary
One of the most common online activities in the European Union in 2014 was participation in social networking [13]. There are many users of social networking sites who are not aware of privacy and often share information without considering who will or will not have access to it [22]. Unlike other proposals that present mechanisms to facilitate the alignment between the expected and the actual audience, in this article we focus on the analysis of the potential reach of a publication in social networks as a consequence of re-sharing actions, assuming that the publication was received by the expected audience. To consider scenarios where third applications cannot have access to the traffic of users’ messages in online social networks, we analyze if there is a correlation between structural network factors and the proposed metrics.
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