cc 15(5): e3

Research Article

A Novel, Privacy Preserving, Architecture for Online Social Networks

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  • @ARTICLE{10.4108/eai.17-12-2015.150806,
        author={Zhe Wang and Naftaly H. Minsky},
        title={A Novel, Privacy Preserving, Architecture for Online Social Networks},
        journal={EAI Endorsed Transactions on Collaborative Computing},
        volume={1},
        number={5},
        publisher={EAI},
        journal_a={CC},
        year={2015},
        month={12},
        keywords={Online social networks; Decentralization; Control; Privacy; Security},
        doi={10.4108/eai.17-12-2015.150806}
    }
    
  • Zhe Wang
    Naftaly H. Minsky
    Year: 2015
    A Novel, Privacy Preserving, Architecture for Online Social Networks
    CC
    EAI
    DOI: 10.4108/eai.17-12-2015.150806
Zhe Wang1, Naftaly H. Minsky1,*
  • 1: Rutgers University, Department of Computer Science
*Contact email: minsky@rutgers.edu

Abstract

The centralized nature of conventional OSNs poses serious risks to the privacy and security of information exchanged between their members. These risks prompted several attempts to create decentralized OSNs, or DOSNs. The basic idea underlying these attempts, is that each member of a social network keeps its data under its own control, instead of surrendering it to a central host, providing access to it to other members according to its own access-control policy. Unfortunately all existing versions of DOSNs have a very serious limitation. Namely, they are unable to subject the membership of a DOSN, and the interaction between its members, to any global policy—which is essential for many social communities. Moreover, the DOSN architecture is unable to support useful capabilities such as narrowcasting and profile based search. This paper describes a novel architecture of decentralized OSNs—called DOSC, for “online social community”. DOSC adopts the decentralization idea underlying DOSNs, but it is able to subject the membership of a DOSC-community, and the interaction between its members, to a wide range of policies, including privacy-preserving narrowcasting and profile-sensitive search.