TY - GEN
T1 - Estimating age privacy leakage in online social networks
AU - Dey, Ratan
AU - Tang, Cong
AU - Ross, Keith
AU - Saxena, Nitesh
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84861651057&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84861651057&partnerID=8YFLogxK
U2 - 10.1109/INFCOM.2012.6195711
DO - 10.1109/INFCOM.2012.6195711
M3 - Conference contribution
AN - SCOPUS:84861651057
SN - 9781467307758
T3 - Proceedings - IEEE INFOCOM
SP - 2836
EP - 2840
BT - 2012 Proceedings IEEE INFOCOM, INFOCOM 2012
T2 - IEEE Conference on Computer Communications, INFOCOM 2012
Y2 - 25 March 2012 through 30 March 2012
ER -