Invention Grant
- Patent Title: Method for detecting if a machine learning model has been copied using intermediate outputs of the machine learning model
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Application No.: US16511082Application Date: 2019-07-15
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Publication No.: US11586989B2Publication Date: 2023-02-21
- Inventor: Joppe Willem Bos , Simon Johann Friedberger , Nikita Veshchikov , Christine Van Vredendaal
- Applicant: NXP B.V.
- Applicant Address: NL Eindhoven
- Assignee: NXP B.V.
- Current Assignee: NXP B.V.
- Current Assignee Address: NL Eindhoven
- Agent Daniel D. Hill
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N20/20 ; G06N3/08

Abstract:
A method is provided for detecting copying of a machine learning model. In the method, the first machine learning model is divided into a plurality of portions. Intermediate outputs from a hidden layer of a selected one of the plurality of portions is compared to corresponding outputs from a second machine learning model to detect the copying. Alternately, a first seal may be generated using the plurality of inputs and the intermediate outputs from nodes of the selected portion. A second seal from a suspected copy that has been generated the same way is compared to the first seal to detect the copying. If the first and second seals are the same, then there is a high likelihood that the suspected copy is an actual copy. By using the method, only the intermediate outputs of the machine learning model outputs have to be disclosed to others, thus protecting the confidentiality of the model.
Public/Granted literature
- US20210019661A1 METHOD FOR DETECTING IF A MACHINE LEARNING MODEL HAS BEEN COPIED Public/Granted day:2021-01-21
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