NDLI: Private social network analysis: how to assemble pieces of a graph privately

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Private social network analysis: how to assemble pieces of a graph privately

Content Provider	ACM Digital Library
Author	Frikken, Keith B. Golle, Philippe
Abstract	Connections in distributed systems, such as social networks, online communities or peer-to-peer networks, form complex graphs. These graphs are of interest to scientists in fields as varied as marketing, epidemiology and psychology. However, knowledge of the graph is typically distributed among a large number of subjects, each of whom knows only a small piece of the graph. Efforts to assemble these pieces often fail because of privacy concerns: subjects refuse to share their local knowledge of the graph. To assuage these privacy concerns, we propose reconstructing the whole graph privately, i.e., in a way that hides the correspondence between the nodes and edges in the graph and the real-life entities and relationships that they represent. We first model the privacy threats posed by the private reconstruction of a distributed graph. Our model takes into account the possibility that malicious nodes may report incorrect information about the graph in order to facilitate later attempts to de-anonymize the reconstructed graph. We then propose protocols to privately assemble the pieces of a graph in ways that mitigate these threats. These protocols severely restrict the ability of adversaries to compromise the privacy of honest subjects.
Starting Page	89
Ending Page	98
Page Count	10
File Format	PDF
ISBN	1595935568
DOI	10.1145/1179601.1179619
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2006-10-30
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Privacy Graph Anonymity Social networks
Content Type	Text
Resource Type	Article

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