Protecting information regarding machine learning models
AssigneeHewlett-Packard Development Company, L.P.
InventorsADRIAN JOHN BALDWIN, PIERRE BELGARRIC, CHRISTOPHER IAN DALTON, DANIEL CAMERON ELLAM, DAVID PLAQUIN
Life of this patent
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Abstract
In an example, an apparatus is described. The apparatus comprises processing circuitry comprising a control module. The control module is to protect information regarding a machine learning model owned by a third party. The information is protected in a memory communicatively coupled to the control module. In response to receiving an indication that a computing device under control of the control module complies with a third party policy associated with the machine learning model, the control module is to release the information to the computing device.
Claims15
An apparatus comprising processing circuitry, the processing circuitry comprising:
- a control module to protect information regarding a machine learning model owned by a third party, where the control module is to protect the information in a memory communicatively coupled to the control module and, in response to receiving an indication that a computing device under control of the control module complies with a third party policy associated with the machine learning model, the control module is to release the information to the computing device.
A tangible machine readable medium comprising instructions which, when executed by at least one processor, cause the at least one processor to:
- receive model information owned by a service provider;
- cause the model information to be securely stored in a memory accessible to a computing device for executing a machine learning model obtained from the model information;
- determine whether or not the computing device can set-up a data processing pipeline to execute the machine learning model in accordance with a model execution condition specified by the service provider;
- and
- in response to determining that the machine learning model can be executed in accordance with the model execution condition, load the machine learning model to the computing device in a format to enable the computing device to execute the machine learning model.
A method, comprising:
- receiving a public portion of a key pair generated by a control module for setting up a data processing pipeline of a computing device, where the key pair is sealed to a measurement obtained by a trusted component of the computing device;
- encrypting information pertaining to a machine learning model under the public portion of the key pair;
- and
- sending the encrypted information and an associated model execution condition to specify how the control module is to set up the data processing pipeline.
Dependencies are inferred from the claim text.