A novel clustering-based anonymization approach for graph to achieve Privacy Preservation in Social Network

DOI

10.2991/ameii-15.2015.102How to use a DOI?

Keywords

Clustering anonymity; -anonymity graph; privacy preservation; social network

Abstract

Serious privacy concern rises with the prosperity of social network applications. To prevent the privacy of vertices or edges associated with entities in a social network from getting re-identified through background information or queries,a novel clustering-based approach is proposed to anonymize vertices and edges. Concepts of vertex similarity matrix and the distance between a vertex and a cluster are defined, based on which a -anonymized graph approach is presented. The effectiveness of the approach is verified Through experiments that compare the performance of our method with that of SASN, an existing anonymization algorithm .

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huowen Jiang
PY  - 2015/04
DA  - 2015/04
TI  - A novel clustering-based anonymization approach for graph to achieve Privacy Preservation in Social Network
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 545
EP  - 549
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.102
DO  - 10.2991/ameii-15.2015.102
ID  - Jiang2015/04
ER  -