SecGraph: a uniform and open-source evaluation system for graph data anonymization and de-anonymization

Abstract

In this paper, we analyze and systematize the state-of-the-art graph data privacy and utility techniques. Specif-ically, we propose and develop SecGraph (available at [1]), a uniform and open-source Secure Graph data sharing/publishing system. In SecGraph, we system-atically study, implement, and evaluate 11 graph data anonymization algorithms, 19 data utility metrics, and 15 modern Structure-based De-Anonymization (SDA) at-tacks. To the best of our knowledge, SecGraph is the first such system that enables data owners to anonymize data by state-of-the-art anonymization techniques, mea-sure the data’s utility, and evaluate the data’s vulnerabil-ity against modern De-Anonymization (DA) attacks. In addition, SecGraph enables researchers to conduct fair analysis and evaluation of existing and newly developed anonymization/DA techniques. Leveraging SecGraph, we conduct extensive experiments to systematically eval-uate the existing graph data anonymization and DA tech-niques. The results demonstrate that (i) most anonymiza-tion schemes can partially or conditionally preserve most graph utilities while losing some application utility; (ii) no DA attack is optimum in all scenarios. The DA performance depends on several factors, e.g., similar-ity between anonymized and auxiliary data, graph den-sity, and DA heuristics; and (iii) all the state-of-the-art anonymization schemes are vulnerable to several or all of the modern SDA attacks. The degree of vulnerability of each anonymization scheme depends on how much and which data utility it preserves. 1