Characterizing and detecting malicious accounts in privacy-centric mobile social networks: A case study
Malicious accounts are one of the biggest threats to the security and privacy of online social
networks (OSNs). In this work, we study a new type of OSN, called privacy-centric mobile …
networks (OSNs). In this work, we study a new type of OSN, called privacy-centric mobile …
On detecting growing-up behaviors of malicious accounts in privacy-centric mobile social networks
Privacy-centric mobile social network (PC-MSN), which allows users to build intimate and
private social circles, is an increasingly popular type of online social networks (OSNs) …
private social circles, is an increasingly popular type of online social networks (OSNs) …
Lbsnshield: Malicious account detection in location-based social networks
Given the popularity of GPS-enabled smart devices, location-based social networks (LBSNs)
have attracted numerous users around the world. The openness of LBSN platforms has also …
have attracted numerous users around the world. The openness of LBSN platforms has also …
Malicious accounts detection from online social networks: a systematic review of literature
I Ben Sassi, S Ben Yahia - International Journal of General …, 2021 - Taylor & Francis
The bourgeoning of Online Social Networks has triggered an increase in undesirable acts
caused by some disruptive entities, eg fake accounts, bots, and cyber-extremists. Thence …
caused by some disruptive entities, eg fake accounts, bots, and cyber-extremists. Thence …
Malicious Account Identification in Social Network Platforms
Today, people of all ages are increasingly using Web platforms for social interaction.
Consequently, many tasks are being transferred over social networks, like advertisements …
Consequently, many tasks are being transferred over social networks, like advertisements …
Uncovering Malicious Accounts in Online Social Networks Using XGBoost and Graph Convolution Networks
Y Tang, D Zhang, KC Li, J Yuan - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In this work, we introduce a Machine-Learning (ML) approach based on XGBoost and Graph
Convolutional Networks (GCNs) for the detection of active malicious accounts in Online …
Convolutional Networks (GCNs) for the detection of active malicious accounts in Online …
A survey on privacy issues in mobile social networks
AMVV Sai, Y Li - IEEE Access, 2020 - ieeexplore.ieee.org
Mobile Social Networks (MSNs) are a category of social networks that have features of both
traditional OSNs and Location-Based Social Networks (LBSNs). MSNs provide users with an …
traditional OSNs and Location-Based Social Networks (LBSNs). MSNs provide users with an …
Mining fraudsters and fraudulent strategies in large-scale mobile social networks
The rapid development of modern communication technologies-in particular,(mobile) phone
communications-has largely facilitated human social interactions and information exchange …
communications-has largely facilitated human social interactions and information exchange …
Detecting clusters of fake accounts in online social networks
C Xiao, DM Freeman, T Hwa - Proceedings of the 8th ACM Workshop on …, 2015 - dl.acm.org
Fake accounts are a preferred means for malicious users of online social networks to send
spam, commit fraud, or otherwise abuse the system. A single malicious actor may create …
spam, commit fraud, or otherwise abuse the system. A single malicious actor may create …
Uncovering Malicious Accounts in Open Mobile Social Networks Using a Graph and Text-Based Attention Fusion Algorithm
In recent years, open mobile social networks focused on socializing and dating purposes
have gained widespread popularity, such as Soul, Tinder, Momo, and Tantan, among …
have gained widespread popularity, such as Soul, Tinder, Momo, and Tantan, among …