公开(公告)号：US20220067075A1

公开(公告)日：2022-03-03

申请号：US17399030

申请日：2021-08-10

Applicant: Apple Inc.

Inventor： Mona CHITNIS ,  Abhishek BHOWMICK ,  Lucas O. WINSTROM ,  Koray MANCUHAN ,  Stephen D. FLEISCHER

IPC: G06F16/335 ,  G06F16/33 ,  G06F21/62 ,  G06F16/16 ,  G06F16/338

Abstract: The subject technology for maintaining differential privacy for database query results receives a query for a database that contains user data. The subject technology determines that the query is permitted for the database based at least in part on a privacy policy associated with the database. The subject technology determines that performing the query will not exceed a query budget for the database. The subject technology, when the query is permitted and performing the query will not exceed the query budget, performs the query on the database and receiving results from the query. The subject technology selects a differential privacy algorithm for the results based at least in part on a query type of the query. The subject technology applies the selected differential privacy algorithm to the results to generate differentially private results. The subject technology provides the differentially private results.

公开(公告)号：US20240028890A1

公开(公告)日：2024-01-25

申请号：US18225656

申请日：2023-07-24

Applicant: Apple Inc.

Inventor： Abhishek BHOWMICK ,  Ryan M. ROGERS ,  Umesh S. VAISHAMPAYAN ,  Andrew H. VYRROS

IPC: G06N3/08 ,  G06N3/04 ,  G06N3/10 ,  G06N3/044 ,  G06N3/045

CPC classification number: G06N3/08 ,  G06N3/04 ,  G06N3/10 ,  G06N3/044 ,  G06N3/045

Abstract: Embodiments described herein provide a technique to crowdsource labeling of training data for a machine learning model while maintaining the privacy of the data provided by crowdsourcing participants. Client devices can be used to generate proposed labels for a unit of data to be used in a training dataset. One or more privacy mechanisms are used to protect user data when transmitting the data to a server. The server can aggregate the proposed labels and use the most frequently proposed labels for an element as the label for the element when generating training data for the machine learning model. The machine learning model is then trained using the crowdsourced labels to improve the accuracy of the model.

公开(公告)号：US20210173856A1

公开(公告)日：2021-06-10

申请号：US16708307

申请日：2019-12-09

Applicant: Apple Inc.

Inventor： Mona CHITNIS ,  Abhishek BHOWMICK ,  Lucas O. WINSTROM ,  Koray MANCUHAN ,  Stephen D. FLEISCHER

IPC: G06F16/335 ,  G06F16/33 ,  G06F16/338 ,  G06F16/16 ,  G06F21/62

Abstract: The subject technology for maintaining differential privacy for database query results receives a query for a database that contains user data. The subject technology determines that the query is permitted for the database based at least in part on a privacy policy associated with the database. The subject technology determines that performing the query will not exceed a query budget for the database. The subject technology, when the query is permitted and performing the query will not exceed the query budget, performs the query on the database and receiving results from the query. The subject technology selects a differential privacy algorithm for the results based at least in part on a query type of the query. The subject technology applies the selected differential privacy algorithm to the results to generate differentially private results. The subject technology provides the differentially private results.