Invention Grant
- Patent Title: Discovery of personal data in machine learning models
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Application No.: US17182271Application Date: 2021-02-23
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Publication No.: US11893132B2Publication Date: 2024-02-06
- Inventor: Abigail Goldsteen , Micha Gideon Moffie , Ariel Farkash
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agent Rakesh Roy
- Main IPC: G06F21/62
- IPC: G06F21/62 ; G06N5/04 ; G06N20/00 ; G06F16/28

Abstract:
A method, computer system, and a computer program product for personal data discovery is provided. The present invention may include determining at least one feature used to train a target machine learning (ML) model. The present invention may also include mapping the determined at least one feature to at least one location of a data store including at least one personal data associated with the determined at least one feature. The present invention may further include retrieving a data record of the at least one personal data associated with the mapped at least one feature from the at least one location of the data store. The present invention may also include determining that the target ML model includes a trace of the retrieved data record. The present invention may further include marking the target ML model as containing the at least one personal data.
Public/Granted literature
- US20220269814A1 DISCOVERY OF PERSONAL DATA IN MACHINE LEARNING MODELS Public/Granted day:2022-08-25
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