Output details
11 - Computer Science and Informatics
University of Warwick
Anonymizing bipartite graph data using safe groupings
<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).