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 …

This article aims to summarize the recent advancement in the fake account detection
methodology on social networking websites. Over the past decade, social networking …

A large-scale dynamically weighted directed network (DWDN) involving numerous entities
and massive dynamic interaction is an essential data source in many big-data-related …

Community affiliation of a node plays an important role in determining its contextual position
in the network, which may raise privacy concerns when a sensitive node wants to hide its …

Graph data is used in a wide range of applications, while analyzing graph data without
protection is prone to privacy breach risks. To mitigate the privacy risks, we resort to the …

One of the most common problems studied in the context of differential privacy for graph
data is counting the number of non-induced embeddings of a subgraph in a given graph …

Multi-label propagation algorithms (MLPAs) aim to find vertex communities in a complex
network or a cloud system by propagating and updating vertex labels, which have been …

Multimodal named entity recognition (MNER) is a crucial task in social systems of artificial
intelligence that requires precise identification of named entities in sentences using both …

While social networking sites gain massive popularity for their friendship networks, user
privacy issues arise due to the incorporation of location‐based services (LBS) into the …

Differential privacy has been widely adopted to release continuous-and scalar-valued
information on a database without compromising the privacy of individual data records in it …