Invention Grant
- Patent Title: Secure machine learning analytics using homomorphic encryption
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Application No.: US17473778Application Date: 2021-09-13
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Publication No.: US11902413B2Publication Date: 2024-02-13
- Inventor: Ellison Anne Williams , Ryan Carr
- Applicant: Enveil, Inc.
- Applicant Address: US MD Fulton
- Assignee: Enveil, Inc.
- Current Assignee: Enveil, Inc.
- Current Assignee Address: US MD Fulton
- Agency: Carr & Ferrell LLP
- Main IPC: H04L9/00
- IPC: H04L9/00 ; H04L9/32 ; G06N20/10 ; G06N3/08 ; G06N5/01

Abstract:
Provided are methods and systems for performing a secure machine learning analysis over an instance of data. An example method includes acquiring, by a client, a homomorphic encryption scheme, and at least one machine learning model data structure. The method further includes generating, using the encryption scheme, at least one homomorphically encrypted data structure, and sending the encrypted data structure to at least one server. The method includes executing a machine learning model, by the at least one server based on the encrypted data structure to obtain an encrypted result. The method further includes sending, by the server, the encrypted result to the client where the encrypted result is decrypted. The machine learning model includes neural networks and decision trees.
Public/Granted literature
- US20210409191A1 Secure Machine Learning Analytics Using Homomorphic Encryption Public/Granted day:2021-12-30
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