Spade: A Real-Time Fraud Detection Framework
Summary: Spade: real-time fraud detection on transaction graphs using incremental dense-subgraph peeling to enable low-latency, scalable updates and higher fraud-prevention ratios versus batch methods. Demo exposes an interactive GUI for algorithm/metric tuning and visual exploration on industrial datasets (Grab, crypto). (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Jiaxin Jiang (National University of Singapore)
- 2. Zhen Zhang (National University of Singapore)
- 3. Bingqiao Luo (National University of Singapore)
- 4. Bingsheng He (National University of Singapore)
- 5. Min Chen (GrabTaxi Holdings)
- 6. WeiYang Wang (GrabTaxi Holdings)
- 7. Jia Chen (GrabTaxi Holdings)
BibTeX Citation
@article{jiang_vldb24,
title = {{Spade: A Real-Time Fraud Detection Framework}},
author = {Jiang, Jiaxin and Zhang, Zhen and Luo, Bingqiao and He, Bingsheng and Chen, Min and Wang, WeiYang and Chen, Jia},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {4253--4256},
doi = {10.14778/3685800.3685848},
url = {https://doi.org/10.14778/3685800.3685848},
year = {2024}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,390 | Spade: A Real-Time Fraud Detection Framework on Evolving Graphs | 2023 | VLDB | 5.4360143e-05 |
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