Community Detection for Access-Control Decisions: Analysing the Role of Homophily and Information Diffusion in Online Social Networks

التفاصيل البيبلوغرافية
العنوان: Community Detection for Access-Control Decisions: Analysing the Role of Homophily and Information Diffusion in Online Social Networks
المؤلفون: Ferreyra, Nicolas E. Diaz, Hecking, Tobias, Aïmeur, Esma, Heisel, Maritta, Hoppe, H. Ulrich
سنة النشر: 2021
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Social and Information Networks, Computer Science - Computers and Society
الوصف: Access-Control Lists (ACLs) (a.k.a. friend lists) are one of the most important privacy features of Online Social Networks (OSNs) as they allow users to restrict the audience of their publications. Nevertheless, creating and maintaining custom ACLs can introduce a high cognitive burden on average OSNs users since it normally requires assessing the trustworthiness of a large number of contacts. In principle, community detection algorithms can be leveraged to support the generation of ACLs by mapping a set of examples (i.e. contacts labelled as untrusted) to the emerging communities inside the user's ego-network. However, unlike users' access-control preferences, traditional community-detection algorithms do not take the homophily characteristics of such communities into account (i.e. attributes shared among members). Consequently, this strategy may lead to inaccurate ACL configurations and privacy breaches under certain homophily scenarios. This work investigates the use of community-detection algorithms for the automatic generation of ACLs in OSNs. Particularly, it analyses the performance of the aforementioned approach under different homophily conditions through a simulation model. Furthermore, since private information may reach the scope of untrusted recipients through the re-sharing affordances of OSNs, information diffusion processes are also modelled and taken explicitly into account. Altogether, the removal of gatekeeper nodes is further explored as a strategy to counteract unwanted data dissemination.
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نوع الوثيقة: Working Paper
DOI: 10.1016/j.osnem.2022.100203
URL الوصول: http://arxiv.org/abs/2104.09137
رقم الأكسشن: edsarx.2104.09137
قاعدة البيانات: arXiv
الوصف
DOI:10.1016/j.osnem.2022.100203