2024-03-29T10:27:20Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1332642016-10-20T09:45:09Zcom_10261_60com_10261_4col_10261_439
2016-06-09T14:11:45Z
urn:hdl:10261/133264
An Algorithm For $k$-Degree Anonymity On Large Networks
Casas, Jordi
Herrera, Jordi
Torra, Vicenç
Data privacy
Network theory
k-degree anonymity
Social networking
Graph theory
In this paper, we consider the problem of anonymization on large networks. There are some anonymization methods for networks, but most of them can not be applied on large networks because of their complexity. We present an algorithm for k-degree anonymity on large networks. Given a network G, we construct a k-degree anonymous network, G, by the minimum number of edge modifications. We devise a simple and efficient algorithm for solving this problem on large networks. Our algorithm uses univariate micro-aggregation to anonymize the degree sequence, and then it modifies the graph structure to meet the k-degree anonymous sequence. We apply our algorithm to a different large real datasets and demonstrate their efficiency and practical utility.
2016-06-09T14:11:45Z
2016-06-09T14:11:45Z
2013-08-25
2016-06-09T14:11:46Z
comunicación de congreso
ASONAM '13 Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 671-675
http://hdl.handle.net/10261/133264
10.1145/2492517.2492643
eng
Sí
closedAccess
Institute of Electrical and Electronics Engineers