Security and Communication Networks

Network Structural Perturbation and its Applications for Controlling Misinformation Diffusion


Publishing date
01 Apr 2022
Status
Closed
Submission deadline
26 Nov 2021

1Sichuan University, Chengdu, China

2Deakin University, Victoria, Australia

3Chongqing University of Posts and Telecommunications, Chongqing, China

This issue is now closed for submissions.
More articles will be published in the near future.

Network Structural Perturbation and its Applications for Controlling Misinformation Diffusion

This issue is now closed for submissions.
More articles will be published in the near future.

Description

Network structural perturbation aims to protect privacy by systematically studying the properties of networks and finding ways to disturb network analysis tools. This prevents the desired or correct analysis results being obtained, which can potentially be used to control the diffusion of misinformation on social networks. Network structure provides an effective representation to characterize entities and the relations between them for online systems, including social network platforms, electronic commerce websites, and computer network systems.

Due to the large volume of network data generated from complex online systems, many network analysis methods have been developed, such as link prediction, community detection, influential node ranking, node classification, and graph summarization. As a result, network privacy can be greatly challenged as the analysis tools obtained from these studies become more sophisticated and widespread and it becomes increasingly possible to infer confidential information. This raises privacy and security-related concerns as our data may be valuable not only to enterprises and public entities but also to cybercriminals who are increasingly relying on such tools for malicious purposes. Therefore, it is of great importance to analyze network structure perturbation methods systematically to mitigate such threats. Furthermore, network structural perturbation can be used to control the spread of misinformation on social networks, thus protecting the security of cyberspace.

This Special Issue aims to provide both theoretical and empirical investigations into network structure perturbation and its application to controlling misinformation spreading. We encourage related original research from different disciplines ranging from computer science, mathematics, and sociology. Furthermore, high-quality review articles describing the current state-of-the-art are also welcome.

Potential topics include but are not limited to the following:

  • Large-scale social/computer network analysis
  • Multiplex/temporal/high-order network analysis
  • Network structural perturbation for large-scale networks
  • Network structural perturbation strategy for microstructures
  • Network structural perturbation strategy for mesoscale structures
  • Assessment of network structural perturbation
  • Prediction network structures
  • Network structural perturbation for controlling misinformation spreading
  • Mathematical models for misinformation spreading

Articles

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  • - Article ID 6945397
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DEDGCN: Dual Evolving Dynamic Graph Convolutional Network

Fengzhe Zhong | Yan Liu | ... | Shunran Duan
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  • - Volume 2022
  • - Article ID 4264489
  • - Research Article

Adaptive Alleviation for Popularity Bias in Recommender Systems with Knowledge Graph

Feng Wei | Shuyu Chen | ... | Yingbo Wu
  • Special Issue
  • - Volume 2022
  • - Article ID 5156086
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LGBM-CBFS: A Heuristic Feature Sampling Method Based on Tree Ensembles

Yu Zhou | Hui Li | Mei Chen
  • Special Issue
  • - Volume 2022
  • - Article ID 1705527
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Enhancing Personalized Recommendation by Transductive Support Vector Machine and Active Learning

Xibin Wang | Yunji Li | ... | Jianfeng Yang
  • Special Issue
  • - Volume 2022
  • - Article ID 7003265
  • - Research Article

A Network Sampling Strategy Inspired by Epidemic Spreading

Qiang Dong | En-Yu Yu | Wen-Jun Li
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  • - Volume 2022
  • - Article ID 2576685
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Dynamical Behavior of Hybrid Propagation of Computer Viruses

Qingyi Zhu | Pingfan Xiang | ... | Chenquan Gan
  • Special Issue
  • - Volume 2022
  • - Article ID 1136144
  • - Research Article

A Novel Tripartite Evolutionary Game Model for Misinformation Propagation in Social Networks

Xianyong Li | Qizhi Li | ... | Yunxia Xu
  • Special Issue
  • - Volume 2022
  • - Article ID 4451304
  • - Research Article

Lag Secure Consensus for Second-Order Nonlinear Multiagent Systems with Event-Triggered Control Strategy under DoS Attacks

Qi Han | Ao Zhang | ... | Yuan Tian
  • Special Issue
  • - Volume 2022
  • - Article ID 4510694
  • - Research Article

Containing Misinformation Spread: A Collaborative Resource Allocation Strategy for Knowledge Popularization and Expert Education

Linhong Li | Kaifan Huang | Xiaofan Yang
  • Special Issue
  • - Volume 2021
  • - Article ID 7999760
  • - Research Article

Spread of Misinformation in Social Networks: Analysis Based on Weibo Tweets

Han Luo | Meng Cai | Ying Cui
Security and Communication Networks
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Article of the Year Award: Outstanding research contributions of 2021, as selected by our Chief Editors. Read the winning articles.