The abuse of community detection algorithms may bring the risk of privacy leakage. To
protect personal privacy in complex networks, community detection attack algorithms are …

Community detection plays an important role in social networks, since it can help to naturally
divide the network into smaller parts so as to simplify network analysis. However, on the …

Community detection has been widely studied from many different perspectives, which
include heuristic approaches in the past and graph neural network in recent years. With …

Community detection, aiming to group nodes based on their connections, plays an important
role in network analysis since communities, treated as meta-nodes, allow us to create a …

Automatic community divisions often facilitate the convenience of rich community
applications such as interest group recommendations. However, it faces a serious …

Community detection techniques seek to find densely connected clusters within large
networks. However, it raises privacy concerns, like the personal reveal or community …

Community structure plays an important role in social networks, which can reveal potential
social relationships and deliver vast economic benefits to enterprises and organizations …

Community detection is a fundamental problem in analyzing the network building principles.
Previous community detections left many security issues that every user in a social network …

The rapid development of community detection algorithms, while serving users in social
networks, also brings about certain privacy problems. In this work, we study community …

Complex social network is a kind of relationship system composed of many nodes according
to social relations. Community detection helps scholars to understand this network topology …