POSTER: Privacy-Preserving Profile Similarity Computation in Online Social Networks

Arjan Jeckmans; Qiang Tang; Pieter H. Hartel

doi:10.1145/2093476.2093495

POSTER: Privacy-Preserving Profile Similarity Computation in Online Social Networks

Arjan Jeckmans, Qiang Tang, Pieter H. Hartel

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Currently, none of the existing online social networks (OSNs) enables its users to make new friends without revealing their private information. This leaves the users in a vulnerable position when searching for new friends. We propose a solution which enables a user to compute her profile similarity with another user in a privacy-preserving way. Our solution is designed for a realistic OSN environment, where a pair of users is unlikely to be online at the same time.

Original language	Undefined
Title of host publication	Proceedings of the 18th ACM conference on Computer and communications security (CCS)
Place of Publication	New York
Publisher	Association for Computing Machinery (ACM)
Pages	793-795
Number of pages	3
ISBN (Print)	978-1-4503-0948-6
DOIs	https://doi.org/10.1145/2093476.2093495
Publication status	Published - Oct 2011
Event	18th ACM conference on Computer and Communications Security, CCS 2011 - Chicago, United States Duration: 17 Oct 2011 → 21 Oct 2011 Conference number: 18

Publication series

Name
Publisher	ACM

Conference

Conference	18th ACM conference on Computer and Communications Security, CCS 2011
Abbreviated title	CCS
Country	United States
City	Chicago
Period	17/10/11 → 21/10/11

Keywords

METIS-284927
SCS-Cybersecurity
EWI-21022
IR-79573

Access to Document

10.1145/2093476.2093495

Cite this

@inproceedings{981acf3554264e95b33a9aedd818df37,

title = "POSTER: Privacy-Preserving Profile Similarity Computation in Online Social Networks",

abstract = "Currently, none of the existing online social networks (OSNs) enables its users to make new friends without revealing their private information. This leaves the users in a vulnerable position when searching for new friends. We propose a solution which enables a user to compute her profile similarity with another user in a privacy-preserving way. Our solution is designed for a realistic OSN environment, where a pair of users is unlikely to be online at the same time.",

keywords = "METIS-284927, SCS-Cybersecurity, EWI-21022, IR-79573",

author = "Arjan Jeckmans and Qiang Tang and Hartel, {Pieter H.}",

note = "10.1145/2093476.2093495 ; null ; Conference date: 17-10-2011 Through 21-10-2011",

year = "2011",

month = oct,

doi = "10.1145/2093476.2093495",

language = "Undefined",

isbn = "978-1-4503-0948-6",

publisher = "Association for Computing Machinery (ACM)",

pages = "793--795",

booktitle = "Proceedings of the 18th ACM conference on Computer and communications security (CCS)",

address = "United States",

}

Jeckmans, A, Tang, Q & Hartel, PH 2011, POSTER: Privacy-Preserving Profile Similarity Computation in Online Social Networks. in Proceedings of the 18th ACM conference on Computer and communications security (CCS). Association for Computing Machinery (ACM), New York, pp. 793-795, 18th ACM conference on Computer and Communications Security, CCS 2011, Chicago, United States, 17/10/11. https://doi.org/10.1145/2093476.2093495

POSTER: Privacy-Preserving Profile Similarity Computation in Online Social Networks. / Jeckmans, Arjan; Tang, Qiang; Hartel, Pieter H.

Proceedings of the 18th ACM conference on Computer and communications security (CCS). New York : Association for Computing Machinery (ACM), 2011. p. 793-795.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - POSTER: Privacy-Preserving Profile Similarity Computation in Online Social Networks

AU - Jeckmans, Arjan

AU - Tang, Qiang

AU - Hartel, Pieter H.

N1 - Conference code: 18

PY - 2011/10

Y1 - 2011/10

N2 - Currently, none of the existing online social networks (OSNs) enables its users to make new friends without revealing their private information. This leaves the users in a vulnerable position when searching for new friends. We propose a solution which enables a user to compute her profile similarity with another user in a privacy-preserving way. Our solution is designed for a realistic OSN environment, where a pair of users is unlikely to be online at the same time.

AB - Currently, none of the existing online social networks (OSNs) enables its users to make new friends without revealing their private information. This leaves the users in a vulnerable position when searching for new friends. We propose a solution which enables a user to compute her profile similarity with another user in a privacy-preserving way. Our solution is designed for a realistic OSN environment, where a pair of users is unlikely to be online at the same time.

KW - METIS-284927

KW - SCS-Cybersecurity

KW - EWI-21022

KW - IR-79573

U2 - 10.1145/2093476.2093495

DO - 10.1145/2093476.2093495

M3 - Conference contribution

SN - 978-1-4503-0948-6

SP - 793

EP - 795

BT - Proceedings of the 18th ACM conference on Computer and communications security (CCS)

PB - Association for Computing Machinery (ACM)

CY - New York

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