research-article

Preserving Relation Privacy in Online Social Network Data

Authors:

Na Li,

Nan Zhang,

Sajal DasAuthors Info & Claims

IEEE Internet Computing, Volume 15, Issue 3

Pages 35 - 42

https://doi.org/10.1109/MIC.2011.26

Published: 01 May 2011 Publication History

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Abstract

Online social networks routinely publish data of interest to third parties, but in so doing often reveal relationships, such as a friendship or contractual association, that an attacker can exploit. This systematic look at existing privacy-preservation techniques highlights the vulnerabilities of users even in networks that completely anonymize identities. Through a taxonomy that categorizes techniques according to the degree of user identity exposure, the authors examine the ways that existing approaches compromise relation privacy and offer more secure alternatives.

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Shetty NMuniyal BDokania ADatta SGandluri MMaben LPriyanshu A(2023)Guarding Your Social CircleSecurity and Communication Networks10.1155/2023/25489622023Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1155/2023/2548962
Park JSung YSharma PJeong YYi G(2017)Novel assessment method for accessing private data in social network security servicesThe Journal of Supercomputing10.1007/s11227-017-2018-673:7(3307-3325)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1007/s11227-017-2018-6
Abawajy JNinggal MHerawan T(2016)Privacy Preserving Social Network Data PublicationIEEE Communications Surveys & Tutorials10.1109/COMST.2016.253366818:3(1974-1997)Online publication date: 1-Jul-2016
https://dl.acm.org/doi/10.1109/COMST.2016.2533668
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Published In

IEEE Internet Computing Volume 15, Issue 3

May 2011

92 pages

ISSN:1089-7801

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IEEE Educational Activities Department

United States

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Published: 01 May 2011

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Shetty NMuniyal BDokania ADatta SGandluri MMaben LPriyanshu A(2023)Guarding Your Social CircleSecurity and Communication Networks10.1155/2023/25489622023Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1155/2023/2548962
Park JSung YSharma PJeong YYi G(2017)Novel assessment method for accessing private data in social network security servicesThe Journal of Supercomputing10.1007/s11227-017-2018-673:7(3307-3325)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1007/s11227-017-2018-6
Abawajy JNinggal MHerawan T(2016)Privacy Preserving Social Network Data PublicationIEEE Communications Surveys & Tutorials10.1109/COMST.2016.253366818:3(1974-1997)Online publication date: 1-Jul-2016
https://dl.acm.org/doi/10.1109/COMST.2016.2533668
Kafalı ÖGünay AYolum P(2014)Detecting and predicting privacy violations in online social networksDistributed and Parallel Databases10.1007/s10619-013-7124-832:1(161-190)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1007/s10619-013-7124-8
White JPark JKamhoua CKwiat KRokne JFaloutsos C(2013)Game theoretic attack analysis in online social network (OSN) servicesProceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1145/2492517.2500257(1012-1019)Online publication date: 25-Aug-2013
https://dl.acm.org/doi/10.1145/2492517.2500257

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Do online social network friends still threaten my privacy?

Towards Privacy-Preserving Data Mining in Online Social Networks: Distance-Grained and Item-Grained Differential Privacy

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