Anonymization is a practical solution for preserving user's privacy in data publishing. Data
owners such as hospitals, banks, social network (SN) service providers, and insurance …

With the widespread use of Internet of things (IoT), mobile phones, connected devices and
artificial intelligence (AI), recommender systems (RSs) have become a booming technology …

Users in various web and mobile applications are vulnerable to attribute inference attacks, in
which an attacker leverages a machine learning classifier to infer a target user's private …

Recommender systems typically require users to reveal their ratings to a recommender
service, which subsequently uses them to provide relevant recommendations. Revealing …

Differential privacy provides strong privacy preservation guarantee in information sharing.
As social network analysis has been enjoying many applications, it opens a new arena for …

Recommender systems are commonly trained on centrally-collected user interaction data
like views or clicks. This practice however raises serious privacy concerns regarding the …