Towards identity anonymization in social networks

k-Symmetry Model: A General Framework To Achieve Identity Anonymization In Social Networks

An Effective Method for Utility Preserving Social Network Graph Anonymization Based on Mathematical Modeling

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...

Hiding Information in Social Networks from De-anonymization Attacks by Using Identity Separation

Social networks allow their users to mark their profile attributes, relationships as private in order to guarantee privacy, although private information get occasionally published within sanitized datasets offered to third parties, such as business partners. Today, powerful deanonymization attacks exist that enable the finding of corresponding nodes within these datasets and public network data...

Social Network De-Anonymization and Privacy Inference with Knowledge Graph Model

Social network data is widely shared, transferred and published for research purposes and business interests, but it has raised much concern on users’ privacy. Even though users’ identity information is always removed, attackers can still de-anonymize users with the help of auxiliary information. To protect against de-anonymization attack, various privacy protection techniques for social networ...

Utility-Oriented K-Anonymization on Social Networks

“Identity disclosure” problem on publishing social network data has gained intensive focus from academia. Existing k-anonymization algorithms on social network may result in nontrivial utility loss. The reason is that the number of the edges modified when anonymizing the social network is the only metric to evaluate utility loss, not considering the fact that different edge modifications have d...