公开(公告)号：US11227063B2

公开(公告)日：2022-01-18

申请号：US17020637

申请日：2020-09-14

Applicant: Apple Inc.

Inventor： Abhishek Bhowmick ,  Andrew H. Vyrros ,  Umesh S. Vaishampayan ,  Kevin W. Decker ,  Conrad Shultz ,  Steve Falkenburg ,  Mateusz Rajca

IPC: H04L29/06 ,  G06F21/62 ,  H04L9/32 ,  H04L29/08 ,  H04W12/02 ,  G06F3/0483 ,  G06F1/28 ,  G06F3/0482

Abstract: Embodiments described herein provide a privacy mechanism to protect user data when transmitting the data to a server that estimates a frequency of such data amongst a set of client devices. In one embodiment, a differential privacy mechanism is implemented using a count-mean-sketch technique that can reduce resource requirements required to enable privacy while providing provable guarantees regarding privacy and utility. For instance, the mechanism can provide the ability to tailor utility (e.g. accuracy of estimations) against the resource requirements (e.g. transmission bandwidth and computation complexity).

公开(公告)号：US20180349637A1

公开(公告)日：2018-12-06

申请号：US15805611

申请日：2017-11-07

Applicant: Apple Inc.

Inventor： Kevin W. Decker ,  Conrad Shultz ,  Steve Falkenburg ,  Mateusz Rajca ,  Abhishek Bhowmick ,  Andrew H. Vyrros ,  Umesh S. Vaishampayan

IPC: G06F21/62 ,  G06F3/0483

Abstract: Embodiments described herein provide a privacy mechanism to protect user data when transmitting the data to a server that estimates a frequency of such data amongst a set of client devices. One embodiment uses a differential privacy mechanism to enhance a user experience by inferring potential user preferences from analyzing crowdsourced user interaction data. Based on a statistical analysis of user interactions in relation to various features or events, development efforts with respect to application behavior may be refined or enhanced. For example, user interactions in relation to the presentation of content such as content from online sources may be analyzed. Accordingly, presentation settings or preferences may be defined based on the crowdsourced user interaction data.

公开(公告)号：US10776511B2

公开(公告)日：2020-09-15

申请号：US15805611

申请日：2017-11-07

Applicant: Apple Inc.

Inventor： Kevin W. Decker ,  Conrad Shultz ,  Steve Falkenburg ,  Mateusz Rajca ,  Abhishek Bhowmick ,  Andrew H. Vyrros ,  Umesh S. Vaishampayan

IPC: H04L29/06 ,  G06F21/62 ,  H04L9/32 ,  H04L29/08 ,  H04W12/02 ,  G06F3/0483 ,  G06F1/28 ,  G06F3/0482

Abstract: Embodiments described herein provide a privacy mechanism to protect user data when transmitting the data to a server that estimates a frequency of such data amongst a set of client devices. One embodiment uses a differential privacy mechanism to enhance a user experience by inferring potential user preferences from analyzing crowdsourced user interaction data. Based on a statistical analysis of user interactions in relation to various features or events, development efforts with respect to application behavior may be refined or enhanced. For example, user interactions in relation to the presentation of content such as content from online sources may be analyzed. Accordingly, presentation settings or preferences may be defined based on the crowdsourced user interaction data.

公开(公告)号：US10599867B2

公开(公告)日：2020-03-24

申请号：US15805591

申请日：2017-11-07

Applicant: Apple Inc.

Inventor： Abhishek Bhowmick ,  Andrew H. Vyrros ,  Umesh S. Vaishampayan ,  Kevin W. Decker ,  Conrad Shultz ,  Steve Falkenburg ,  Mateusz Rajca

IPC: H04L29/08 ,  G06F21/62 ,  H04L29/06 ,  G06F3/0483 ,  G06F1/28 ,  G06F3/0482

Abstract: Embodiments described herein provide a privacy mechanism to protect user data when transmitting the data to a server that estimates a frequency of such data amongst a set of client devices. In one embodiment, a differential privacy mechanism is implemented using a count-mean-sketch technique that can reduce resource requirements required to enable privacy while providing provable guarantees regarding privacy and utility. For instance, the mechanism can provide the ability to tailor utility (e.g. accuracy of estimations) against the resource requirements (e.g. transmission bandwidth and computation complexity).