Fraud Detection through Graph-Based User Behavior Modeling

    ACM Conference on Computer and Communications Security, 2015.

    Cited by: 10|Bibtex|Views14|Links
    EI

    Abstract:

    How do anomalies, fraud, and spam effect our models of normal user behavior? How can we modify our models to catch fraudsters? In this tutorial we will answer these questions - connecting graph analysis tools for user behavior modeling to anomaly and fraud detection. In particular, we will focus on three data mining techniques: subgraph a...More

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