Recently, a huge amount of social networks have been made publicly available. In parallel,
several definitions and methods have been proposed to protect users' privacy when publicly …

In recent decades, social network anonymization has become a crucial research field due to
its pivotal role in preserving users' privacy. However, the high diversity of approaches …

In this article we provide a formal framework for reidentification in general. We define n-
confusion as a concept for modeling the anonymity of a database table and we prove that n …

In this paper, we tackle the problem of graph anonymization in the context of privacy-
preserving social network mining. We present a greedy and non-deterministic algorithm to …

It is a challenging problem to preserve friendly-correlations between individuals when
publishing social network data. To alleviate this problem, uncertain graph has been …

Data privacy breaches have prompted growing concerns regarding privacy issues on social
networks. Preserving the privacy of links in the directed social graph, where edges signify …

The growing popularity of social networks and the increasing need for publishing related
data mean that protection of privacy becomes an important and challenging problem in …

In this paper, we tackle the problem of graph generalization in the context of privacy-
preserving social network mining. By grouping together nodes that are not only similar but …

Graphs can be used as a model for online social networks. In this framework, vertices
represent individuals and edges relationships between individuals. In recent years, different …

In this paper we present an overview of the results obtained by our research group within the
area of data privacy. Results focus on data-driven problems (respondent and owner privacy …