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US 12,010,208 B2Granted
Multiple data source secure data processing
AssigneeVia Science, Inc.
InventorsKai Chung Cheung, Mathew Rogers, Jeremy Taylor
Life of this patent
Estimating the term…
Abstract
Multiple systems may determine neural-network output data and neural-network parameter data and may transmit the data therebetween to train and run the neural-network model to predict an event given input data. A data-provider system may perform a dot-product operation using encrypted data, and a secure-processing component may decrypt and process that data using an activation function to predict an event. Multiple secure-processing components may be used to perform a multiplication operation using homomorphic encrypted data.
Claims20
A computer-implemented method comprising:
- processing, by a first system using an input layer of a neural-network model, first input data to determine first feature data, the input layer corresponding to first neural-network parameters;
- receiving, by the first system, encrypted second neural-network parameters corresponding to an output layer of the neural-network model;
- processing, by the first system using a multiplication operation, the first feature data and the encrypted second neural-network parameters to determine encrypted multiplication data;
- sending, from the first system to a second system, the encrypted multiplication data;
- and
- receiving, by the first system and from the second system, event data corresponding to the first input data, wherein the event data is determined using the output layer of the neural-network model and based at least in part on the encrypted multiplication data.
3 more elements
A system comprising:
- at least one processor;
- and
- at least one memory including instructions that, when executed by the at least one processor, cause the system to:
- process, by a first system using an input layer of a neural-network model, first input data to determine first feature data, the input layer corresponding to first neural-network parameters;
- receive, by the first system, encrypted second neural-network parameters corresponding to an output layer of the neural-network model;
- process, by the first system using a multiplication operation, the first feature data and the encrypted second neural-network parameters to determine encrypted multiplication data;
- send, from the first system to a second system, the encrypted multiplication data;
- and
- receive, by the first system and from the second system, event data corresponding to the first input data, wherein the event data is determined using the output layer of the neural-network model and based at least in part on the encrypted multiplication data.
6 more elements
Dependencies are inferred from the claim text.