This paper presents sequential clustering algorithms for anonymizing social networks. Those algorithms produce anonymizations by means of clustering with better utility than those achieved by existing algorithms. We devised a secure distributed version of our algorithms for the case in which the network data is split between several players. We focused on the scenario in which the interacting players know the identity of all nodes in the network, but need to protect the structural information. To the best of our knowledge, this is the first study of privacy preservation in distributed social networks. We conclude by outlining future research proposals in that direction.
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