Invention Grant
- Patent Title: Privacy preserving synthetic string generation using recurrent neural networks
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Application No.: US16836528Application Date: 2020-03-31
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Publication No.: US12008141B2Publication Date: 2024-06-11
- Inventor: Liron Hayman , Shlomi Medalion
- Applicant: Intuit Inc.
- Applicant Address: US CA Mountain View
- Assignee: Intuit Inc.
- Current Assignee: Intuit Inc.
- Current Assignee Address: US CA Mountain View
- Agency: Lathrop GPM LLP
- Main IPC: G06F21/62
- IPC: G06F21/62 ; G06N3/084 ; G06N20/00

Abstract:
A method for privacy preserving synthetic string generation using recurrent neural networks includes receiving input data that includes a plurality of strings with private information. A neural network model is trained using the plurality of strings. The neural network model includes a recurrent neural network (RNN). An anonymous string is generated with the neural network model after training the neural network model with the plurality of strings from the input data. The anonymous string is validated to preclude the private information from the anonymous string. Anonymous data is transmitted that includes the anonymous string and precludes the private information in response to a request for the anonymous data.
Public/Granted literature
- US20210303726A1 PRIVACY PRESERVING SYNTHETIC STRING GENERATION USING RECURRENT NEURAL NETWORKS Public/Granted day:2021-09-30
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