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11 - Computer Science and Informatics

University of Warwick

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Article title

Anonymizing bipartite graph data using safe groupings

Type

D - Journal article

DOI

10.1007/s00778-009-0167-9

Title of journal

The VLDB Journal

Article number

Volume number

Issue number

First page of article

115

ISSN of journal

0949-877X

Year of publication

2010

URL

http://link.springer.com/article/10.1007%2Fs00778-009-0167-9#page-1

Number of additional authors

Additional information

<19> This paper was an invited contribution to a special issue of the VLDBJ, one of the top-three journals in database research, for the six best papers presented at the 2008 VLDB conference. With over 100 citations, the new techniques for the effective anonymisation of graph data are subject to a US patent application (20110041184) and have impacted on research on identity anonymisation in graphs (Miklau, Stanford; Yao, Rutgers; Das, Microsoft Research), privacy preservation (Pei, Simon Fraser University), de-identifying unstructured medical data (Xiong, Emory), relationship privacy preservation (Das, U. Texas), anonymisation of multi-graphs (Aggarwal, IBM Research), identity obfuscation (Bonchi, Yahoo! Research).

Interdisciplinary

Cross-referral requested

Research group

S - Systems and Software

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract