Nowadays, partly driven by many Web 2.0 applications, more and more social network data has been made publicly available and analyzed in one way or another. Privacy preserving publishing of social network data becomes a more and more important concern. In this paper, we present a brief yet systematic review of the existing anonymization techniques for privacy preserving publishing of social network data. We identify the new challenges in privacy preserving publishing of social network data comparing to the extensively studied relational case, and examine the possible problem formulation in three important dimensions: privacy, background knowledge, and data utility. We survey the existing anonymization methods for privacy preservation in two categories: clustering-based approaches and graph modification approaches.
Description
A brief survey on anonymization techniques for privacy preserving publishing of social network data
%0 Journal Article
%1 zhou2008brief
%A Zhou, Bin
%A Pei, Jian
%A Luk, WoShun
%C New York, NY, USA
%D 2008
%I ACM
%J SIGKDD Explor. Newsl.
%K an anonymization privacy social-networks survey
%P 12--22
%R 10.1145/1540276.1540279
%T A brief survey on anonymization techniques for privacy preserving publishing of social network data
%U http://doi.acm.org/10.1145/1540276.1540279
%V 10
%X Nowadays, partly driven by many Web 2.0 applications, more and more social network data has been made publicly available and analyzed in one way or another. Privacy preserving publishing of social network data becomes a more and more important concern. In this paper, we present a brief yet systematic review of the existing anonymization techniques for privacy preserving publishing of social network data. We identify the new challenges in privacy preserving publishing of social network data comparing to the extensively studied relational case, and examine the possible problem formulation in three important dimensions: privacy, background knowledge, and data utility. We survey the existing anonymization methods for privacy preservation in two categories: clustering-based approaches and graph modification approaches.
@article{zhou2008brief,
abstract = {Nowadays, partly driven by many Web 2.0 applications, more and more social network data has been made publicly available and analyzed in one way or another. Privacy preserving publishing of social network data becomes a more and more important concern. In this paper, we present a brief yet systematic review of the existing anonymization techniques for privacy preserving publishing of social network data. We identify the new challenges in privacy preserving publishing of social network data comparing to the extensively studied relational case, and examine the possible problem formulation in three important dimensions: privacy, background knowledge, and data utility. We survey the existing anonymization methods for privacy preservation in two categories: clustering-based approaches and graph modification approaches.},
acmid = {1540279},
added-at = {2011-03-28T11:54:03.000+0200},
address = {New York, NY, USA},
author = {Zhou, Bin and Pei, Jian and Luk, WoShun},
biburl = {https://www.bibsonomy.org/bibtex/2225a71310c5714969ea2f1bb286b6b02/beate},
description = {A brief survey on anonymization techniques for privacy preserving publishing of social network data},
doi = {10.1145/1540276.1540279},
interhash = {281931699aaab48376c72c0a8260567d},
intrahash = {225a71310c5714969ea2f1bb286b6b02},
issn = {1931-0145},
issue = {2},
journal = {SIGKDD Explor. Newsl.},
keywords = {an anonymization privacy social-networks survey},
month = {December},
numpages = {11},
pages = {12--22},
publisher = {ACM},
timestamp = {2011-03-28T11:54:03.000+0200},
title = {A brief survey on anonymization techniques for privacy preserving publishing of social network data},
url = {http://doi.acm.org/10.1145/1540276.1540279},
volume = 10,
year = 2008
}