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Mathematical Problems in Engineering
Volume 2013, Article ID 237024, 8 pages
Research Article

Structural Attack to Anonymous Graph of Social Networks

School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China

Received 19 June 2013; Revised 7 October 2013; Accepted 18 October 2013

Academic Editor: Siddhivinayak Kulkarni

Copyright © 2013 Tieying Zhu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


With the rapid development of social networks and its applications, the demand of publishing and sharing social network data for the purpose of commercial or research is increasing. However, the disclosure risks of sensitive information of social network users are also arising. The paper proposes an effective structural attack to deanonymize social graph data. The attack uses the cumulative degree of -hop neighbors of a node as the regional feature and combines it with the simulated annealing-based graph matching method to explore the nodes reidentification in anonymous social graphs. The simulation results on two social network datasets show that the attack is feasible in the nodes reidentification in anonymous graphs including the simply anonymous graph, randomized graph and -isomorphism graph.