Preserving the d-Reachability When Anonymizing Social Networks

Abstract

The goal of graph anonymization is avoiding disclosure of privacy in social networks through graph modifications meanwhile preserving data utility of anonymized graphs for social network analysis. Graph reachability is an important data utility as reachability queries are not only common on graph databases, but also serving as fundamental operations for many other graph queries. However, the graph reachability is severely distorted after anonymization. In this work, we study how to preserve the d-reachability of vertices when anonymizing social networks. We solve the problem by designing a d-reachability preserving graph anonymization (d-RPA for short) algorithm. The main idea of d-RPA is to find a subgraph that preserves the d-reachability, and keep it unchanged during anonymization. We show that d-RPA can efficiently find such a subgraph and anonymize the releasing graph with low information loss. Extensive experiments on real datasets illustrate that anonymized social networks generated by our method can be used to answer d-reachable queries with high accuracy.