Evaluating the security of anonymized big graph/structural data
We studied the security of anonymized big graph data. Our main contributions include: new De-Anonymization (DA) attacks, comprehensive anonymity, utility, and de-anonymizability quantifications, and a secure graph data publishing/sharing system SecGraph. New DA Attacks. We present two novel graph DA...
Main Author: | |
---|---|
Other Authors: | |
Format: | Others |
Language: | en_US |
Published: |
Georgia Institute of Technology
2016
|
Subjects: | |
Online Access: | http://hdl.handle.net/1853/54913 |