Estimation of privacy risk through centrality metrics
نویسندگان
چکیده
منابع مشابه
Estimation of privacy risk through centrality metrics
Users are not often aware of privacy risks and disclose information in online social networks. They do not consider the audience that will have access to it or the risk that the information continues to spread and may reach an unexpected audience. Moreover, not all users have the same perception of risk. To overcome these issues, we propose a Privacy Risk Score (PRS) that: (1) estimates the rea...
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Acquiring the full global information is impractical, if feasible at all, in many networks with distributed operation and self-organization features. To meet scalability requirements practical protocol implementations could use local information instead, drawn from the nodes’ ego-networks, the Social Network Analysis (SNA) counterpart of centered graphs. However, in almost all these efforts the...
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Centrality indices are an essential concept in network analysis. For those based on shortest-path distances the computation is at least quadratic in the number of nodes, since it usually involves solving the single-source shortest-paths (SSSP) problem from every node. Therefore, exact computation is infeasible for many large networks of interest today. Centrality scores can be estimated, howeve...
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ژورنال
عنوان ژورنال: Future Generation Computer Systems
سال: 2018
ISSN: 0167-739X
DOI: 10.1016/j.future.2017.12.030