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Community detection for access-control decisions : analysing the role of homophily and information diffusion in online social networks

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  • معلومة اضافية
    • Publisher Information:
      Elsevier 2022-03-14T12:46:31Z 2022-03-14T12:46:31Z 2022-05
    • نبذة مختصرة :
      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.
    • الموضوع:
      Access control; Community detection; Homophily; Information diffusion; Online social networks; cs.SI; Computer Science - Computers and Society; 004: Informatik; Journal Article; Other; Other; Journal Article
    • Availability:
      Open access content. Open access content
      https://creativecommons.org/licenses/by/4.0
      false
    • Note:
      application/pdf
      English
    • Other Numbers:
      H9H oai:tore.tuhh.de:11420/11987
      Online Social Networks and Media 29: 100203 (2022-05)
      10.15480/882.4239
      2104.09137v2
      2-s2.0-85125593106
      1308800972
    • Contributing Source:
      TECHNISCHE UNIVERSITAT HAMBURG-HARBURG
      From OAIster®, provided by the OCLC Cooperative.
    • الرقم المعرف:
      edsoai.on1308800972
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