TY - JOUR
ID - 81694
TI - An Effective Method for Utility Preserving Social Network Graph Anonymization Based on Mathematical Modeling
JO - International Journal of Engineering
JA - IJE
LA - en
SN - 1025-2495
AU - Mortazavi, R.
AU - Erfani, S. H.
AD - School of Engineering, Damghan University, Damghan, Iran
Y1 - 2018
PY - 2018
VL - 31
IS - 10
SP - 1624
EP - 1632
KW - Mathematical Modeling
KW - graph anonymization
KW - graph modification
KW - social network
KW - Privacy
KW - Database Security
DO -
N2 - In recent years, privacy concerns about social network graph data publishing has increased due to the widespread use of such data for research purposes. This paper addresses the problem of identity disclosure risk of a node assuming that the adversary identifies one of its immediate neighbors in the published data. The related anonymity level of a graph is formulated and a mathematical model is proposed to solve the problem. The application of the method on a number of synthetic and real-world datasets confirms that the method is general and can be used in different contexts to produce superior results in terms of the utility of the anonymized graph.
UR - http://www.ije.ir/article_81694.html
L1 - http://www.ije.ir/article_81694_e3849caf4384bbe53aed25f3afd8d93e.pdf
ER -