Invention Grant
- Patent Title: Multiple input neural networks for detecting fraud
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Application No.: US15665301Application Date: 2017-07-31
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Publication No.: US11372956B2Publication Date: 2022-06-28
- Inventor: Gleb Esman
- Applicant: Splunk Inc.
- Applicant Address: US CA San Francisco
- Assignee: Splunk Inc.
- Current Assignee: Splunk Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Artegis Law Group, LLP
- Main IPC: G06F21/31
- IPC: G06F21/31 ; G06F21/32 ; G06N3/02 ; G06N3/04 ; G06N3/08

Abstract:
Embodiments of the present invention set forth a technique for predicting fraud based on multiple inputs including user behavior biometric data along with one or more other parameters associated with the user. The technique includes receiving cursor movement data generated via a client device. The technique further includes generating a image based on the cursor movement data. The technique further includes receiving client parameters generated via the client device. The technique further includes analyzing the image and the client parameters based on a model to generate a prediction result, where the model is generated based on second cursor movement data and a second set of client parameters associated with a first group of one or more users. The technique further includes determining, based on the prediction result, that a user of the client device is not a member of the first group.
Public/Granted literature
- US20180300465A1 MULTIPLE INPUT NEURAL NETWORKS FOR DETECTING FRAUD Public/Granted day:2018-10-18
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