NDLI: The union-split algorithm and cluster-based anonymization of social networks

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The union-split algorithm and cluster-based anonymization of social networks

Content Provider	ACM Digital Library
Author	Yao, Danfeng Thompson, Brian
Abstract	Knowledge discovery on social network data can uncover latent social trends and produce valuable findings that benefit the welfare of the general public. A growing amount of research finds that social networks play a surprisingly powerful role in people's behaviors. Before the social network data can be released for research purposes, the data needs to be anonymized to prevent potential re-identification attacks. Most of the existing anonymization approaches were developed for relational data, and cannot be used to handle social network data directly. In this paper, we model social networks as undirected graphs and formally define privacy models, attack models for the anonymization problem, in particular an i-hop degree-based anonymization problem, i.e., the adversary's prior knowledge includes the target's degree and the degrees of neighbors within i hops from the target. We present two new and efficient clustering methods for undirected graphs: bounded t-means clustering and union-split clustering algorithms that group similar graph nodes into clusters with a minimum size constraint. These clustering algorithms are contributions beyond the specific social network problems studied and can be used to cluster general data types besides graph vertices. We also develop a simple-yet-effective inter-cluster matching method for anonymizing social networks by strategically adding and removing edges based on nodes' social roles. We carry out a series of experiments to evaluate the graph utilities of the anonymized social networks produced by our algorithms.
Starting Page	218
Ending Page	227
Page Count	10
File Format	PDF
ISBN	9781605583945
DOI	10.1145/1533057.1533088
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-03-10
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Clustering algorithms Social networks Social role Graph anonymization
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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