Estimating age privacy leakage in online social networks

Ratan Dey, Cong Tang, Keith Ross, Nitesh Saxena

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


    We perform a large-scale study to quantify just how severe the privacy leakage problem is in Facebook. As a case study, we focus on estimating birth year, which is a fundamental human attribute and, for many people, a private one. Specifically, we attempt to estimate the birth year of over 1 million Facebook users in New York City. We examine the accuracy of estimation procedures for several classes of users: (i) highly private users, who do not make their friend lists public; (ii) users who hide their birth years but make their friend lists public. To estimate Facebook users' ages, we exploit the underlying social network structure to design an iterative algorithm, which derives age estimates based on friends' ages, friends of friends' ages, and so on. We find that for most users, including highly private users who hide their friend lists, it is possible to estimate ages with an error of only a few years. We also make a specific suggestion to Facebook which, if implemented, would greatly reduce privacy leakages in its service.

    Original languageEnglish (US)
    Title of host publication2012 Proceedings IEEE INFOCOM, INFOCOM 2012
    Number of pages5
    StatePublished - 2012
    EventIEEE Conference on Computer Communications, INFOCOM 2012 - Orlando, FL, United States
    Duration: Mar 25 2012Mar 30 2012

    Publication series

    NameProceedings - IEEE INFOCOM
    ISSN (Print)0743-166X


    OtherIEEE Conference on Computer Communications, INFOCOM 2012
    Country/TerritoryUnited States
    CityOrlando, FL

    ASJC Scopus subject areas

    • General Computer Science
    • Electrical and Electronic Engineering

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