Awesome-Deep-Graph-Anomaly-Detection
A collection of papers on deep learning for graph anomaly detection, and published algorithms and datasets.
- Awesome-Deep-Graph-Anomaly-Detection
A Timeline of graph anomaly detection
Surveys
Anomalous Node Detection
Anomalous Edge Detection
Paper Title | Venue | Year | Model | Code |
---|---|---|---|---|
Anomaly Detection in Dynamic Graphs via Transformer | TKDE | 2021 | TADDY | [Code] |
efraudcom: An e-commerce fraud detection system via competitive graph neural networks | IS | 2021 | efraudcom | [Code] |
Unified graph embedding-based anomalous edge detection | IJCNN | 2020 | - | - |
AANE: Anomaly aware network embedding for anomalous link detection | ICDM | 2020 | AANE | - |
Addgraph: Anomaly detection in dynamic graph using attention-based temporal gcn | IJCAI | 2019 | Addgraph | - |
Netwalk: A flexible deep embedding approach for anomaly detection in dynamic networks | SIGKDD | 2018 | Netwalk | [Code] |
Anomalous Sub-graph Detection
Paper Title | Venue | Year | Model | Code |
---|---|---|---|---|
SliceNDice: Mining suspicious multi-attribute entity groups with multi-view graphs | arXiv | 2020 | SliceNDice | [Code] |
Deep structure learning for fraud detection | ICDM | 2018 | DeepFD | [Code] |
Fraudne: A joint embedding approach for fraud detection | IJCNN | 2018 | FraudNE | - |
Anomalous Graph-Level Detection
Paper Title | Venue | Year | Model | Code |
---|---|---|---|---|
User preference-aware fake news detection | SIGIR | 2021 | UPFD | [Code] |
On using classification datasets to evaluate graph outlier detection: Peculiar observations and new insights | arXiv | 2021 | OCGIN | [Code] |
Glad-paw: Graph-based log anomaly detection by position aware weighted graph attention network | PAKDD | 2021 | Glad-paw | - |
Deep into hypersphere: Robust and unsupervised anomaly discovery in dynamic networks | IJCAI | 2018 | DeepSphere | [Code] |
Graph-Based Anomaly Detection Methods
Paper Title | Venue | Year | Model | Code |
---|---|---|---|---|
Detecting rumours with latency guarantees using massive streaming data | VLDB J. | 2022 | - | - |
Graph Neural Networks for Anomaly Detection in Industrial Internet of Things | IEEE Internet of Things Journal | 2022 | - | - |
Dynamic Graph-Based Anomaly Detection in the Electrical Grid | Trans. Power Syst. | 2021 | - | [Code] |
Nonparametric Anomaly Detection on Time Series of Graphs | J. Comput. Graph. Stat. | 2021 | - | [Code] |
NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification | SSDBM | 2021 | NF-GNN | - |
Open-sourced Graph Anomaly Detection Libraries
Library | Link |
---|---|
pygod | [Github] |
DGFraud | [Github] |
Datasets
Mostly-used Benchmark Datasets
- BlogCatalog https://github.com/XiaoxiaoMa-MQ/Awesome-Deep-Graph-Anomaly-Detection/tree/main/Datasets
- ACM https://github.com/XiaoxiaoMa-MQ/Awesome-Deep-Graph-Anomaly-Detection/tree/main/Datasets
- Flickr https://github.com/XiaoxiaoMa-MQ/Awesome-Deep-Graph-Anomaly-Detection/tree/main/Datasets
Citation/Co-authorship Networks
- Citeseer, Cora, Pubmed https://linqs.soe.ucsc.edu/data
- DBLP http://snap.stanford.edu/data/com-DBLP.html, http://www.informatik.uni-trier.de/ ̃ley/db/
- ACM http://www.arnetminer.org/open-academic-graph
Social Networks
- Enron http://odds.cs.stonybrook.edu/#table2
- UCI Message http://archive.ics.uci.edu/ml
- Google+ https://wangbinghui.net/dataset.html
- Twitter Sybil https://wangbinghui.net/dataset.html
- Twitter World-Cup2014 http://shebuti.com/SelectiveAnomalyEnsemble/
- Twitter Security2014 http://shebuti.com/SelectiveAnomalyEnsemble/
- Reality Mining http://shebuti.com/SelectiveAnomalyEnsemble/
- NYTNews http://shebuti.com/SelectiveAnomalyEnsemble/
- Politifact https://github.com/safe-graph/GNN-FakeNews
- Gossipcop https://github.com/safe-graph/GNN-FakeNews
Co-purchasing Networks
- Disney Calls https://www.ipd.kit.edu/mitarbeiter/muellere/consub/
- Amazon-v1 https://www.ipd.kit.edu/mitarbeiter/muellere/consub/
- Amazon-v2 https://github.com/dmlc/dgl/blob/master/python/dgl/data/fraud.py
- Elliptic https://www.kaggle.com/ellipticco/elliptic-data-set
- Yelp https://github.com/dmlc/dgl/blob/master/python/dgl/data/fraud.py
Transportation Networks
- New York City Taxi http://www.nyc.gov/html/tlc/html/about/triprecorddata.shtml
Tools
- Gephi https://gephi.org/
- Pajek http://mrvar.fdv.uni-lj.si/pajek/
- LFR https://www.santofortunato.net/resources
Disclaimer
If you have any questions or updated news on graph anomaly detection, please feel free to contact us. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors and boost further research in this area.
Emails: xiaoxiao.ma2@hdr.mq.edu.au, jia.wu@mq.edu.au.