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An alert system to avoid financial fraud

In the modern information society online transactions are an important part of our daily lives. In this work we present an alert system that determines the current threat level of financial fraud in the internet. We use data from different sources and off-the-shelf machine learning algorithms to compute the current threat level. Based on the threat level our alert system issues alerts to raise users awareness of current attack vectors. We tested our approaches with real world online banking frauds. Our preliminary results suggest that this mechanisms can be effectively used to warn users about the current threat situation and therefore help avoiding financial fraud.

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