Privacy-Preserving network aggregation

Authors:
Troy Raeder;Marina Blanton;Nitesh V. Chawla;Keith Frikken
Affiliations:
Interdisciplinary Center for Network Science and Applications, University of Notre Dame, Notre Dame, IN;Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN;Interdisciplinary Center for Network Science and Applications, University of Notre Dame, Notre Dame, IN;Miami University, Oxford, OH
Venue:
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Year:
2010

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Abstract

Consider the scenario where information about a large network is distributed across several different parties or commercial entities. Intuitively, we would expect that the aggregate network formed by combining the individual private networks would be a more faithful representation of the network phenomenon as a whole. However, privacy preservation of the individual networks becomes a mandate. Thus, it would be useful, given several portions of an underlying network p1 ...pn, to securely compute the aggregate of all the networks pi in a manner such that no party learns information about any other party's network. In this work, we propose a novel privacy preservation protocol for the non-trivial case of weighted networks. The protocol is secure against malicious adversaries.