Surrogate Parenthood: Protected and Informative Graphs
Barbara Blaustein (MITRE), Adriane Chapman (MITRE), Len Seligman, (MITRE), M. David Allen (MITRE), Arnon Rosenthal (MITRE)

TL;DR
This paper introduces techniques for creating protected, surrogate-enhanced graph representations that preserve connectivity and informativeness while safeguarding sensitive information, enabling more useful path-based queries.
Contribution
It formalizes the problem of generating protected graph accounts using surrogates, introduces utility and opacity measures, and provides an algorithm to maximize information retention.
Findings
Surrogates improve graph query informativeness.
Protected accounts maintain connectivity with minimal performance impact.
Evaluation shows added value without significant overhead.
Abstract
Many applications, including provenance and some analyses of social networks, require path-based queries over graph-structured data. When these graphs contain sensitive information, paths may be broken, resulting in uninformative query results. This paper presents innovative techniques that give users more informative graph query results; the techniques leverage a common industry practice of providing what we call surrogates: alternate, less sensitive versions of nodes and edges releasable to a broader community. We describe techniques for interposing surrogate nodes and edges to protect sensitive graph components, while maximizing graph connectivity and giving users as much information as possible. In this work, we formalize the problem of creating a protected account G' of a graph G. We provide a utility measure to compare the informativeness of alternate protected accounts and an…
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Taxonomy
TopicsScientific Computing and Data Management · Distributed systems and fault tolerance · Privacy-Preserving Technologies in Data
