Identifying on-line Fraudsters: Anomaly Detection Using Network Effects
by Christos Faloutsos
Description:
Detecting anomalies and fraud has important applications in finance,
online commerce, healthcare, law enforcement etc.
Using network effects ('guilt by association')
with large data sets is becoming increasingly effective
in a range of analyses from identifying fraudulent transactions
to uncovering social media players engaged in artificially boosting networks.
Foils
Here