Call For Paper Volume:4 Issue:6 Jun'2017

Anonymization of Social Networks for Reducing Communication Complexity and Information loss by Sequential Clustering

Publication Date : 10/05/2015



Author(s) :

Nirav U. Patel , Vaishali R. Patel.


Volume/Issue :
Volume 2
,
Issue 5
(05 - 2015)



Abstract :

Privacy Preserving Publishing in Social Network is always an important Concern. In Recent Years, the impact of social networks on society, the people become more sensitive regarding privacy issues in the Social networks. The goal of the proposed work is to arrive at an anonymized view of the social networks without revealing to any information about the nodes and links between nodes that are controlled by the data holders. The main contributions in this paper are Hierarchical algorithm for anonymizing a social network and a measure that quantifies the information loss in the anonymization process to preserve privacy. The anonymized dataset permits strong attacks due to lack of diversity in the sensitive attributes. This paper uses the t-closeness, a framework that gives stronger privacy guarantees.


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Anonymization of Social Networks for Reducing Communication Complexity and Information loss by Sequential Clustering

May 6, 2015