safe-graph / Graph Fraud Detection Papers
A curated list of fraud detection papers using graph information or graph neural networks
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Graph-based Fraud Detection Papers and Resources
A curated list of fraud detection papers using graph information or graph neural networks
GNN Papers
2021
| Year | Title | Venue | Paper | Code |
|---|---|---|---|---|
| 2021 | Few-shot Network Anomaly Detection via Cross-network Meta-learning | WWW 2021 | Link | Link |
| 2021 | Towards Consumer Loan Fraud Detection: Graph Neural Networks with Role-Constrained Conditional Random Field | AAAI 2021 | Link | Link |
2020
| Year | Title | Venue | Paper | Code |
|---|---|---|---|---|
| 2020 | Suspicious Massive Registration Detection via Dynamic Heterogeneous Graph Neural Networks | AAAI 2021 Workshop | Link | Link |
| 2020 | APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding | arXiv | Link | Link |
| 2020 | Metagraph Aggregated Heterogeneous Graph Neural Network for Illicit Traded Product Identification in Underground Market | ICDM 2020 | Link | Link |
| 2020 | Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection | ICDM 2020 | Link | Link |
| 2020 | Heterogeneous Mini-Graph Neural Network and Its Application to Fraud Invitation Detection | ICDM 2020 | Link | Link |
| 2020 | xFraud: Explainable Fraud Transaction Detection on Heterogeneous Graphs | arXiv | Link | Link |
| 2020 | BotSpot: A Hybrid Learning Framework to Uncover Bot Install Fraud in Mobile Advertising | CIKM 2020 | Link | Link |
| 2020 | Early Anomaly Detection by Learning and Forecasting Behavior | arXiv | Link | Link |
| 2020 | ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks | arXiv | Link | Link |
| 2020 | Multivariate Time-series Anomaly Detection via Graph Attention Network | ICDM 2020 | Link | Link |
| 2020 | GFD: A Weighted Heterogeneous Graph Embedding Based Approach for Fraud Detection in Mobile Advertising | Security and Communication Networks | Link | Link |
| 2020 | Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters | CIKM 2020 | Link | Link |
| 2020 | Graph-based Modeling of Online Communities for Fake News Detection | arXiv | Link | Link |
| 2020 | FANG: Leveraging Social Context for Fake News Detection Using Graph Representation | CIKM 2020 | Link | Link |
| 2020 | Loan Default Analysis with Multiplex Graph Learning | CIKM 2020 | Link | Link |
| 2020 | Error-Bounded Graph Anomaly Loss for GNNs | CIKM 2020 | Link | Link |
| 2020 | GCNEXT: graph convolutional network with expanded balance theory for fraudulent user detection | Social Network Analysis and Mining | Link | Link |
| 2020 | FauxWard: a graph neural network approach to fauxtography detection using social media comments | Social Network Analysis and Mining | Link | Link |
| 2020 | A Scalable Framework for Group Fraud Detection in Transaction using Deep Graph Neural Network | [email protected] 2020 | Link | Link |
| 2020 | Early Fraud Detection with Augmented Graph Learning | [email protected] 2020 | Link | Link |
| 2020 | TIES: Temporal Interaction Embeddings For Enhancing Social Media Integrity At Facebook | KDD 2020 | Link | Link |
| 2020 | DETERRENT: Knowledge Guided Graph Attention Network for Detecting Healthcare Misinformation | KDD 2020 | Link | Link |
| 2020 | Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection | SIGIR 2020 | Link | Link |
| 2020 | GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media | ACL 2020 | Link | Link |
| 2020 | Camouflaged Chinese Spam Content Detection with Semi-supervised Generative Active Learning | ACL 2020 | Link | Link |
| 2020 | DFraud3-Multi-Component Fraud Detection free of Cold-start | arXiv | Link | Link |
| 2020 | Financial Risk Analysis for SMEs with Graph-based Supply Chain Mining | IJCAI 2020 | Link | Link |
| 2020 | Rumor Detection on Social Media with Graph Structured Adversarial Learning | IJCAI 2020 | Link | Link |
| 2020 | GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection | SIGIR 2020 | Link | Link |
| 2020 | ASA: Adversary Situation Awareness via Heterogeneous Graph Convolutional Networks | WWW 2020 Workshop | Link | Link |
| 2020 | Graph Convolutional Networks with Markov Random Field Reasoning for Social Spammer Detection | AAAI 2020 | Link | Link |
| 2020 | Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks | AAAI 2020 | Link | Link |
Before 2019
| Year | Title | Venue | Paper | Code |
|---|---|---|---|---|
| 2019 | A Semi-supervised Graph Attentive Network for Fraud Detection | ICDM 2019 | Link | Link |
| 2019 | Detect Camouflaged Spam Content via StoneSkipping: Graph and Text Joint Embedding for Chinese Character Variation Representation | EMNLP 2019 | Link | Link |
| 2019 | Key Player Identification in Underground Forums over Attributed Heterogeneous Information Network Embedding Framework | CIKM 2019 | Link | Link |
| 2019 | Spam Review Detection with Graph Convolutional Networks | CIKM 2019 | Link | Link |
| 2019 | Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics | KDD 2019 Workshop | Link | Link |
| 2019 | Uncovering Insurance Fraud Conspiracy with Network Learning | SIGIR 2019 | Link | Link |
| 2019 | FdGars: Fraudster Detection via Graph Convolutional Networks in Online App Review System | WWW 2019 Workshop | Link | Link |
| 2019 | GeniePath: Graph Neural Networks with Adaptive Receptive Paths | AAAI 2019 | Link | Link |
| 2018 | Heterogeneous Graph Neural Networks for Malicious Account Detection | CIKM 2018 | Link | Link |
| 2018 | GraphRAD: A Graph-based Risky Account Detection System | MLG 2018 | Link | Link |
Non-GNN Papers since 2014
| Year | Title | Venue | Paper | Code |
|---|---|---|---|---|
| 2020 | Network Inference from a Mixture of Diffusion Models for Fake News Mitigation | ICWSM 2021 | Link | Link |
| 2020 | Uncovering Coordinated Networks on Social Media | ICWSM 2021 | Link | Link |
| 2020 | AUTOAUDIT: Mining Accounting and Time-Evolving Graphs | IEEE BigData 2020 | Link | Link |
| 2020 | SpecGreedy: Unified Dense Subgraph Detection | ECML-PKDD 2020 | Link | Link |
| 2020 | Real-Time Streaming Anomaly Detection in Dynamic Graphs | arXiv | Link | Link |
| 2020 | Robust Spammer Detection by Nash Reinforcement Learning | KDD 2020 | Link | Link |
| 2020 | KNH: Multi-View Modeling with K-Nearest Hyperplanes Graph for Misinformation Detection | [email protected] 2020 | Link | Link |
| 2020 | Collaboration Based Multi-Label Propagation for Fraud Detection | IJCAI 2020 | Link | Link |
| 2020 | Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitation | ICWSM 2020 | Link | Link |
| 2020 | Friend or Faux: Graph-Based Early Detection of Fake Accounts on Social Networks | WWW 2020 | Link | Link |
| 2020 | Financial Defaulter Detection on Online Credit Payment via Multi-view Attributed Heterogeneous Information Network | WWW 2020 | Link | Link |
| 2020 | MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams | AAAI 2020 | Link | Link |
| 2020 | EnsemFDet: An Ensemble Approach to Fraud Detection based on Bipartite Graph | arXiv | Link | Link |
| 2020 | FlowScope: Spotting Money Laundering Based on Graphs | AAAI 2020 | Link | Link |
| 2019 | SliceNDice: Mining Suspicious Multi-attribute Entity Groups with Multi-view Graphs | DSAA 2019 | Link | Link |
| 2019 | TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial | VLDB 2019 | Link | Link |
| 2019 | Spotting Collective Behaviour of Online Frauds in Customer Reviews | IJCAI 2019 | Link | Link |
| 2019 | Cash-Out User Detection Based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism | AAAI 2019 | Link | Link |
| 2018 | Deep Structure Learning for Fraud Detection | ICDM 2018 | Link | Link |
| 2018 | FeatNet: Large-scale Fraud Device Detection by Network Representation Learning with Rich Features | AiSec 2018 | Link | Link |
| 2018 | HGsuspector: Scalable Collective Fraud Detection in Heterogeneous Graphs | KDD 2018 Workshop | Link | Link |
| 2018 | Online E-Commerce Fraud: A Large-scale Detection and Analysis | ICDE 2018 | Link | Link |
| 2018 | Combating Crowdsourced Review Manipulators: A Neighborhood-Based Approach | WSDM 2018 | Link | Link |
| 2018 | REV2: Fraudulent User Prediction in Rating Platforms | WSDM 2018 | Link | Link |
| 2017 | ZooBP: Belief Propagation for Heterogeneous Networks | VLDB 2017 | Link | Link |
| 2017 | HitFraud: A Broad Learning Approach for Collective Fraud Detection in Heterogeneous Information Networks | ICDM 2017 | Link | Link |
| 2017 | GANG: Detecting Fraudulent Users in Online Social Networks via Guilt-by-Association on Directed Graph | ICDM 2017 | Link | Link |
| 2017 | The Many Faces of Link Fraud | ICDM 2017 | Link | Link |
| 2017 | HoloScope: Topology-and-Spike Aware Fraud Detection | CIKM 2017 | Link | Link |
| 2017 | iBGP: A Bipartite Graph Propagation Approach for Mobile Advertising Fraud Detection | Mobile Information Systems 2017 | Link | Link |
| 2016 | FRAUDAR: Bounding Graph Fraud in the Face of Camouflage | KDD 2016 | Link | Link |
| 2015 | Collective Opinion Spam Detection: Bridging Review Networks and Metadata | KDD 2015 | Link | Link |
| 2014 | Spotting Suspicious Link Behavior with fBox: An Adversarial Perspective | ICDM 2014 | Link | Link |
Useful Resources
DGFraud: A Deep Graph-based Toolbox for Fraud Detection
UGFraud: An Unsupervised Graph-based Toolbox for Fraud Detection
Awesome Fraud Detection Research Papers
Outlier Detection DataSets (ODDS)
Graph Fraud Datasets from Prof. Srijan Kumar
Bitcoin Fraudulent Transaction Dataset
Mobile App Install Fraud Dataset
Graph Adversarial Learning Literature
Survey Papers
Graph based anomaly detection and description: a survey
Adversarial Attack and Defense on Graph Data: A Survey
Suspicious behavior detection: Current trends and future directions
False information on web and social media: A survey
Misinformation in Social Media: Definition, Manipulation, and Detection
Mining Disinformation and Fake News: Concepts, Methods, and Recent Advancements
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