Abstract
Liu and Terzi proposed the notion of k-degree anonymity to address the problem of identity anonymization in graphs. A graph is k-degree anonymous if and only if each of its vertices has the same degree as that of, at least, k-1 other vertices. The anonymization problem is to transform a non-k-degree anonymous graph into a k-degree anonymous graph by adding or deleting a minimum number of edges.
Liu and Terzi proposed an algorithm that remains a reference for k-degree anonymization. The algorithm consists of two phases. The first phase anonymizes the degree sequence of the original graph. The second phase constructs a k-degree anonymous graph with the anonymized degree sequence by adding edges to the original graph. In this work, we propose a greedy algorithm that anonymizes the original graph by simultaneously adding edges to the original graph and anonymizing its degree sequence. We thereby avoid testing the realizability of the degree sequence, which is a time consuming operation. We empirically and comparatively evaluate our new algorithm. The experimental results show that our algorithm is indeed more efficient and more effective than the algorithm proposed by Liu and Terzi on large real graphs.
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Lu, X., Song, Y., Bressan, S. (2012). Fast Identity Anonymization on Graphs. In: Liddle, S.W., Schewe, KD., Tjoa, A.M., Zhou, X. (eds) Database and Expert Systems Applications. DEXA 2012. Lecture Notes in Computer Science, vol 7446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32600-4_21
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DOI: https://doi.org/10.1007/978-3-642-32600-4_21
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