Privacy Preserving Social Network Publication on Bipartite Graphs

Abstract : In social networks, some data may come in the form of bipartite graphs, where properties of nodes are public while the associations between two nodes are private and should be protected. When publishing the above data, in order to protect privacy, we propose to adopt the idea generalizing the graphs to super-nodes and super-edges. We investigate the problem of how to preserve utility as much as possible and propose an approach to partition the nodes in the process of generalization. Our approach can give privacy guarantees against both static attacks and dynamic attacks, and at the same time effectively answer aggregate queries on published data.
Document type :
Conference papers
Complete list of metadatas

Cited literature [16 references]  Display  Hide  Download

https://hal.inria.fr/hal-01534307
Contributor : Hal Ifip <>
Submitted on : Wednesday, June 7, 2017 - 3:03:40 PM
Last modification on : Friday, November 3, 2017 - 10:24:07 PM
Long-term archiving on : Friday, September 8, 2017 - 12:47:18 PM

File

978-3-642-30955-7_7_Chapter.pd...
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Jian Zhou, Jiwu Jing, Ji Xiang, Lei Wang. Privacy Preserving Social Network Publication on Bipartite Graphs. 6th International Workshop on Information Security Theory and Practice (WISTP), Jun 2012, Egham, United Kingdom. pp.58-70, ⟨10.1007/978-3-642-30955-7_7⟩. ⟨hal-01534307⟩

Share

Metrics

Record views

672

Files downloads

98