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 …

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 …

Data collected nowadays by social-networking applications create fascinating opportunities
for building novel services, as well as expanding our understanding about social structures …

Privacy is one of the most important issues in social social network data sharing. Structure
anonymization is a effective method to protect user from being reidentfied through graph …

Bu tez bireylerin farklı kişilik özellikleri, motivasyonları ve kullanım durumları arasındaki olası
ilişkileri anlamak ve her birinin reklama yönelik genel tutum üzerindeki etkisini ortaya …

Analyzing the structure of social networks is of interest in a wide range of disciplines.
Unfortunately, sharing social-network datasets is often restrained by privacy considerations …

Due to the increasing cost of data storage and computation, more and more graphs (eg, web
graphs, social networks) are outsourced and analyzed in the cloud. However, there is …

Liu and Terzi proposed the notion of k-degree anonymity to address the problem of identity
anonymization in graphs. A graph is k-degree anonymous if and only if each of its vertices …