Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-23556-6_3
Title: LORA: Link obfuscation by randomization in graphs
Authors: Xiao, Q.
Wang, Z.
Tan, K.-L. 
Keywords: Hierarchical Random Graph
Link Entropy
Link Obfuscation
Issue Date: 2011
Source: Xiao, Q.,Wang, Z.,Tan, K.-L. (2011). LORA: Link obfuscation by randomization in graphs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6933 LNCS : 33-51. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-23556-6_3
Abstract: In this paper, we propose a randomization scheme, LORA (Link Obfuscation by Randomization), to obfuscate edge existence in graphs. Specifically, we extract the source graph's hierarchical random graph model and reconstruct the released graph randomly with this model. We show that the released graph can preserve critical graph statistical properties even after a large number of edges have been replaced. To measure the effectiveness of our scheme, we introduce the notion of link entropy to quantify its privacy-preserving strength wrt the existence of edges. © 2011 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/41726
ISBN: 9783642235559
ISSN: 03029743
DOI: 10.1007/978-3-642-23556-6_3
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