US 12,470,381 B2
Controlling execution of machine learning models
Adrian John Baldwin, Bristol (GB); Christopher Ian Dalton, Bristol (GB); Pierre Belgarric, Bristol (GB); David Plaquin, Bristol (GB); and Daniel Cameron Ellam, Bristol (GB)
Assigned to Hewlett-Packard Development Company, L.P., Spring, TX (US)
Appl. No. 18/249,164
Filed by Hewlett-Packard Development Company, L.P., Spring, TX (US)
PCT Filed Oct. 29, 2020, PCT No. PCT/US2020/058013
§ 371(c)(1), (2) Date Apr. 14, 2023,
PCT Pub. No. WO2022/093240, PCT Pub. Date May 5, 2022.
Prior Publication US 2023/0396435 A1, Dec. 7, 2023
Int. Cl. H04L 9/30 (2006.01); G06N 20/00 (2019.01)
CPC H04L 9/30 (2013.01) [G06N 20/00 (2019.01)] 21 Claims
OG exemplary drawing
 
1. An apparatus comprising processing circuitry, the processing circuitry comprising:
an attestation module to:
operate in a control plane of a data processing pipeline, and
generate a cryptographically signed attestation based on a model execution specification that defines a specified state for executing a machine learning model controlled by a third party entity; and
a control module to:
operate in the control plane of the data processing pipeline,
determine whether a computing device communicatively coupled to the control module is in the specified state, and
send, to the attestation module in response to determining that the computing device is in the specified state, an indication that the computing device is in the specified state.