mlsanityData to 7 Oct 2026

Cost Sensitive GNN-based Imbalanced Learning for Mobile Social Network Fraud Detection

arXiv 2303.17486 ↗First posted 28 Mar 2023cs.SI cs.AI cs.LGcited by 12

Not on the map. Why?

Abstract (arXiv)

With the rapid development of mobile networks, the people's social contacts have been considerably facilitated. However, the rise of mobile social network fraud upon those networks, has caused a great deal of distress, in case of depleting personal and social wealth, then potentially doing significant economic harm. To detect fraudulent users, call detail record (CDR) data, which portrays the social behavior of users in mobile networks, has been widely utilized. But the imbalance problem in the aforementioned data, which could severely hinder the effectiveness of fraud detectors based on graph neural networks(GNN), has hardly been addressed in previous work. In this paper, we are going to present a novel Cost-Sensitive Graph Neural Network (CSGNN) by creatively combining cost-sensitive learning and graph neural networks. We conduct extensive experiments on two open-source realworld mobile network fraud datasets. The results show that CSGNN can effectively solve the graph imbalance problem and then achieve better detection performance than the state-of-the-art algorithms. We believe that our research can be applied to solve the graph imbalance problems in other fields. The CSGNN code and datasets are publicly available at https://github.com/xxhu94/CSGNN.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 18 of its 74 references that are in the map. First posted on arXiv 28 Mar 2023.

Builds on

18 of 74 references.

References · 18

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  2. 2017Graph Attention Networkscited by 8,854
  3. 2017Inductive Representation Learning on Large Graphscited by 6,284
  4. 2020Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsterscited by 248
  5. 2015Cost Sensitive Learning of Deep Feature Representations from Imbalanced Datacited by 167
  6. 2018Adaptive Graph Convolutional Neural Networkscited by 155
  7. 2020A Semi-supervised Graph Attentive Network for Financial Fraud Detectioncited by 150
  8. 2021GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networkscited by 147
  9. 2020Heterogeneous Graph Neural Networks for Malicious Account Detectioncited by 95
  10. 2020Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detectioncited by 81
  11. 2018GeniePath: Graph Neural Networks with Adaptive Receptive Pathscited by 66
  12. 2021GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Predictioncited by 36
6 more
  1. 2021Imbalanced Graph Classification via Graph-of-Graph Neural Networkscited by 27
  2. 2020Network Embedding with Completely-imbalanced Labelscited by 21
  3. 2022Graph Neural Network with Curriculum Learning for Imbalanced Node Classificationcited by 19
  4. 2019Deep Iterative and Adaptive Learning for Graph Neural Networkscited by 17
  5. 2021Distance-wise Prototypical Graph Neural Network in Node Imbalance Classificationcited by 16
  6. 2019Neural Similarity Learningcited by 13

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 3; 2025: 5; 2026: 2.

12 papers.

  1. 2024Graph Neural Networks for Financial Fraud Detection: A Reviewcited by 24
  2. 2023GAT-COBO: Cost-Sensitive Graph Neural Network for Telecom Fraud Detectioncited by 5
  3. 2023Single Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learningcited by 3
  4. 2026CAMERA: Adapting to Semantic Camouflage in Unsupervised Text-Attributed Graph Fraud Detectioncited by 3
  5. 2024Twisted Convolutional Networks (TCNs): Enhancing Feature Interactions for Non-Spatial Data Classificationcited by 1
  6. 2025Heterogeneous Graph Prompt Learning via Adaptive Weight Pruningcited by 1
  7. 2024SFR-GNN: Simple and Fast Robust GNNs against Structural Attackscited by 0
  8. 2025Graph Neural Network-based Spectral Filtering Mechanism for Imbalance Classification in Network Digital Twincited by 0
  9. 2025Corporate Fraud Detection in Rich-yet-Noisy Financial Graphcited by 0
  10. 2025Supervised Graph Contrastive Learning for Gene Regulatory Networkscited by 0
  11. 2025SEASONED: Semantic-Enhanced Self-Counterfactual Explainable Detection of Adversarial Exploiter Contractscited by 0
  12. 2026Neuromorphic Graph Anomaly Detection via Adaptive STDP and Spiking Graph Neural Networkscited by 0