Utility-Oriented K-Anonymization on Social Networks

"Identity disclosure" problem on publishing social network data has gained intensive focus from academia. Existing k-anonymization algorithms on social network may result in nontrivial utility loss. The reason is that the number of the edges modified when anonymizing the social network is...

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Main Authors: WANG, Yazhe, XIE, Long, ZHENG, Baihua, LEE, Ken C. K.
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Language:English
Published: Institutional Knowledge at Singapore Management University 2011
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Online Access:https://ink.library.smu.edu.sg/sis_research/1408
https://ink.library.smu.edu.sg/context/sis_research/article/2407/viewcontent/ZhangBHDASFAA11.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-24072018-12-07T01:03:50Z Utility-Oriented K-Anonymization on Social Networks WANG, Yazhe XIE, Long ZHENG, Baihua LEE, Ken C. K. "Identity disclosure" problem on publishing social network data has gained intensive focus from academia. Existing k-anonymization algorithms on social network may result in nontrivial utility loss. The reason is that the number of the edges modified when anonymizing the social network is the only metric to evaluate utility loss, not considering the fact that different edge modifications have different impact on the network structure. To tackle this issue, we propose a novel utility-oriented social network anonymization scheme to achieve privacy protection with relatively low utility loss. First, a proper utility evaluation model is proposed. It focuses on the changes on social network topological feature, but not purely the number of edge modifications. Second, an efficient algorithm is designed to anonymize a given social network with relatively low utility loss. Experimental evaluation shows that our approach effectively generates anonymized social network with high utility. 2011-04-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1408 info:doi/10.1007/978-3-642-20149-3_8 https://ink.library.smu.edu.sg/context/sis_research/article/2407/viewcontent/ZhangBHDASFAA11.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer Sciences Databases and Information Systems Social Media
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Computer Sciences
Databases and Information Systems
Social Media
spellingShingle Computer Sciences
Databases and Information Systems
Social Media
WANG, Yazhe
XIE, Long
ZHENG, Baihua
LEE, Ken C. K.
Utility-Oriented K-Anonymization on Social Networks
description "Identity disclosure" problem on publishing social network data has gained intensive focus from academia. Existing k-anonymization algorithms on social network may result in nontrivial utility loss. The reason is that the number of the edges modified when anonymizing the social network is the only metric to evaluate utility loss, not considering the fact that different edge modifications have different impact on the network structure. To tackle this issue, we propose a novel utility-oriented social network anonymization scheme to achieve privacy protection with relatively low utility loss. First, a proper utility evaluation model is proposed. It focuses on the changes on social network topological feature, but not purely the number of edge modifications. Second, an efficient algorithm is designed to anonymize a given social network with relatively low utility loss. Experimental evaluation shows that our approach effectively generates anonymized social network with high utility.
format text
author WANG, Yazhe
XIE, Long
ZHENG, Baihua
LEE, Ken C. K.
author_facet WANG, Yazhe
XIE, Long
ZHENG, Baihua
LEE, Ken C. K.
author_sort WANG, Yazhe
title Utility-Oriented K-Anonymization on Social Networks
title_short Utility-Oriented K-Anonymization on Social Networks
title_full Utility-Oriented K-Anonymization on Social Networks
title_fullStr Utility-Oriented K-Anonymization on Social Networks
title_full_unstemmed Utility-Oriented K-Anonymization on Social Networks
title_sort utility-oriented k-anonymization on social networks
publisher Institutional Knowledge at Singapore Management University
publishDate 2011
url https://ink.library.smu.edu.sg/sis_research/1408
https://ink.library.smu.edu.sg/context/sis_research/article/2407/viewcontent/ZhangBHDASFAA11.pdf
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