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Tracking Fraudulent Mouse Movements

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Mouse movements could help identify users with fraudulent intentions.

Credit: Getty Images

An international research team led by Markus Weinmann at the University of Cologne identified online fraudsters by their mouse movements, which were longer and slower than those of honest users.

The researchers analyzed mouse movements or trace data over time by assigning participants different tasks. Participants who made fraudulent responses were much slower and made greater deviant mouse movements than honest users on average. The researchers estimate that fraudsters deviated 20% to 42% more, and were concurrently 15% to 26% slower moving their mice, than honest users. Their work will be published in MIS Quarterly.

"Most systems designed to detect fraud only analyze fraud [that] has been committed," Weinmann says. "We offer a method that complements existing methods by enabling fraud checks to be carried out in real time."

From University of Cologne
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