Modern cyber physical systems (CPSs) has widely being used in our daily lives because of
development of information and communication technologies (ICT). With the provision of …

Nowadays, many computer and communication systems generate graph data. Graph data
span many different domains, ranging from online social network data from networks like …

The objective of machine learning is to extract useful information from data, while privacy is
preserved by concealing information. Thus it seems hard to reconcile these competing …

Graph structured data have enabled several successful applications such as
recommendation systems and traffic prediction, given the rich node features and edges …

The increasing popularity of social media has attracted a huge number of people to
participate in numerous activities on a daily basis. This results in tremendous amounts of …

Due to the close correlation with individual's physical features and status, the adoption of
cyber-physical social systems (CPSSs) has been inevitably hindered by users' privacy …

Local business service systems (LBSS), such as Yelp and Dianping, play an essential role
in making decisions like choosing a restaurant for our daily life. These systems heavily rely …

Local differential privacy (LDP) is an emerging technique for privacy-preserving data
collection without a trusted collector. Despite its strong privacy guarantee, LDP cannot be …

The rapid evolution of the Internet of Things (IoT) paradigm during the last decade has lead
to its adoption in critical infrastructure. However, the multitude of benefits that are derived …

Currently, lots of real social relations in social networks force users to face the potential risk
of privacy leakage. Consequently, data holders would like to disturbor anonymize their …