The introduction of online social networks (OSN) has transformed the way people connect
and interact with each other as well as share information. OSN have led to a tremendous …

In this paper, we present a comprehensive survey of privacy-preserving big data analytics.
We introduce well-designed taxonomies which offer both systematic views and a detailed …

Social network analysis has gained significant attention in recent years, largely due to the
success of online social networking and media-sharing sites, and the consequent …

Recently, more and more social network data have been published in one way or another.
Preserving privacy in publishing social network data becomes an important concern. With …

Online social network providers have become treasure troves of information for marketers
and researchers. To profit from their data while honoring the privacy of their customers …

Enabling accurate analysis of social network data while preserving differential privacy has
been challenging since graph features such as cluster coefficient often have high sensitivity …

Social networks have received dramatic interest in research and development. In this
chapter, we survey the very recent research development on privacypreserving publishing of …

We study the problem of privacy-preservation in social networks. We consider the distributed
setting in which the network data is split between several data holders. The goal is to arrive …

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 social networks, by removing some target-sensitive links, privacy protection might be
achieved. However, some hidden links can still be re-observed by link prediction methods …