Intuit, Inc.

Gabriel Goldman

Liron Hayman

Yaron Moshe

Ariel Simhon

Uri Lapidot

A method for detecting fraudulent financial transactions in information technology networks involves obtaining a multitude of features associated with a financial transaction conducted over an information technology network by an unknown transaction party. The multitude of features includes clickstream data obtained from the unknown transaction party. The clickstream data is associated with data of the financial transaction being entered by the unknown transaction party. The method further involves obtaining a first fraud indicator using a machine learning classifier operating on the multitude of features, obtaining a second fraud indicator using a rule-based classifier operating on the multitude of features, obtaining a fraud prediction for the financial transaction, using the first fraud indicator and the second fraud indicator, and taking an action, in response to the fraud prediction.

Method and system for detecting fraudulent transactions in information technology networks

A processor may receive clear text data. The processor may represent at least a portion of the clear text data as at least one array encoding a description of at least one feature of the clear text data. The processor may process the at least one array using a clustering algorithm to determine whether the at least one array is grouped with a benign cluster or a sensitive cluster of a model. In response to determining that the at least one array is grouped with the sensitive cluster, the processor may generate an alert indicating that the clear text data includes sensitive information.

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Hod Hasharon, Israel

Gabriel Goldman