FDM Secure Mining of Association Rules in Horizontally Distributed Databases

Provided by: International Journal of Engineering Trends and Technology
Topic: Security
Format: PDF
The authors study the problem of privacy-preservation in social networks. They consider the distributed setting in which the network data is split between several data holders. The goal is to arrive at an anonymized view of the unified network without revealing to any of the data holders information about links between nodes that are controlled by other data holders. To that end, they start with the centralized setting and offer two variants of an anonymization algorithm which is based on Sequential clustering (Sq). Their algorithms significantly outperform the SaNGreeA algorithm due to Campan and Truta which is the leading algorithm for achieving anonymity in networks by means of clustering.

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