Joining user profiles across online social networks: From the perspective of an adversary

Qiang Ma, Han Hee Song, S. Muthukrishnan, Antonio Nucci

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Being the anchor points for building social relationships in the cyberspace, online social networks (OSNs) play an integral part of modern peoples life. Since different OSNs are designed to address specific social needs, people take part in multiple OSNs to cover different facets of their life. While the fragmented pieces of information about a user in each OSN may be of limited use, serious privacy issues arise if a sophisticated adversary pieces information together from multiple OSNs. To this end, we undertake the role of such an adversary and demonstrate the possibility of 'splicing' user profiles across multiple OSNs and present associated security risks to users. In doing so, we develop a scalable and systematic profile joining scheme, Splicer, that focuses on various aspects of profile attributes by simultaneously performing exact, quasi-perfect and partial matches between pairs of profiles. From our evaluations on three real OSN data, Splicer not only handles large-scale OSN profiles efficiently by saving 87% computation time compared to all-pair profile comparisons, but also far exceeds the recall of generic distance measure based approach at the same precision level by 33%. Finally, we quantify the amount of information 'lift' attributed to joining of OSNs, where on average 22% additional profile attributes can be added to 24% of users.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
    EditorsRavi Kumar, James Caverlee, Hanghang Tong
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages178-185
    Number of pages8
    ISBN (Electronic)9781509028467
    DOIs
    StatePublished - Nov 21 2016
    Event2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States
    Duration: Aug 18 2016Aug 21 2016

    Publication series

    NameProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

    Conference

    Conference2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
    CountryUnited States
    CitySan Francisco
    Period8/18/168/21/16

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Sociology and Political Science
    • Communication

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