Encrypted machine learning models
AssigneeAmazon Technologies, Inc.
InventorsYuanjun Xiong, Jia Bi Zhang, Bing Shuai, Juan Pablo Escalona Garcia
Life of this patent
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Abstract
A machine learning model, such as a neural network, is partially encrypted with a homomorphic encryption scheme. Application of the machine learning model to data includes performing operations on plaintext and encrypting results of operations for input to other operations that are performed over cyphertext. Ciphertext output of such operations can be provided to a service that is able to decrypt the ciphertext output.
Claims19
A computer-implemented method, comprising:
- obtaining input data to be processed using a machine learning model, the obtained input data being in plaintext form;
- using a first portion of the machine learning model, comprising a first set of layers of a neural network, to calculate plaintext intermediate data, the first portion of the machine learning model, comprising a second set of layers of the neural network, in plaintext form and a second portion of the machine learning model in ciphertext form according to a homomorphic encryption scheme;
- using the homomorphic encryption scheme to encrypt the plaintext intermediate data to obtain ciphertext intermediate data;
- using the second portion of the machine learning model to obtain, without decrypting the ciphertext intermediate data, encrypted output data according to the homomorphic encryption scheme;
- and
- transmitting a request to a service to cause the service to decrypt the encrypted output data and provide corresponding plaintext output data in response to the request.
A system, comprising:
- one or more processors;
- and
- memory that stores computer-executable instructions that are executable by the one or more processors to cause the system to:
- obtain data indicating a portion of a machine learning model, comprising a set of layers of a neural network, to encrypt;
- obtain a partially encrypted machine learning model by at least encrypting the portion of the model using a cipher of a homomorphic encryption scheme;
- and
- provide the partially encrypted machine learning model to a device that lacks an ability to decrypt the encrypted portion of the partially encrypted machine learning model.
A non-transitory computer-readable storage medium storing thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to:
- obtain ciphertext input data based on plaintext input data, the ciphertext input data being output a cipher of a homomorphic encryption scheme;
- obtain ciphertext output data by at least applying a first portion of a machine learning model to the ciphertext input data, the machine learning model comprising the first portion with a first set of layers of a neural network, and a second portion with a second set of layers of the neural network, the first portion being encrypted according to the homomorphic encryption scheme and the second portion being in plaintext form;
- and
- obtain plaintext output data by causing the ciphertext output data to be decrypted.
Dependencies are inferred from the claim text.