View source for 17924897. PRIVACY-PRESERVING CROSS-DOMAIN EXPERIMENTAL GROUP PARTITIONING AND MONITORING simplified abstract (GOOGLE LLC)

=PRIVACY-PRESERVING CROSS-DOMAIN EXPERIMENTAL GROUP PARTITIONING AND MONITORING=


==Organization Name==

[[:Category:GOOGLE LLC|GOOGLE LLC]]


[[Category:GOOGLE LLC]]

==Inventor(s)==

[[:Category:Gang Wang of Frederick MD (US)|Gang Wang of Frederick MD (US)]][[Category:Gang Wang of Frederick MD (US)]]

[[:Category:Marcel M. Moti Yung of New York NY (US)|Marcel M. Moti Yung of New York NY (US)]][[Category:Marcel M. Moti Yung of New York NY (US)]]

[[:Category:Timothy David Lambert of Ontario (CA)|Timothy David Lambert of Ontario (CA)]][[Category:Timothy David Lambert of Ontario (CA)]]

==PRIVACY-PRESERVING CROSS-DOMAIN EXPERIMENTAL GROUP PARTITIONING AND MONITORING - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17924897 titled 'PRIVACY-PRESERVING CROSS-DOMAIN EXPERIMENTAL GROUP PARTITIONING AND MONITORING

==Simplified Explanation==
The patent application describes methods, systems, and apparatus for privacy-preserving cross-domain experiment monitoring using secure multi-party computation (MPC) systems.

* Receiving a request for digital content with an application instance identifier.
* Conducting a privacy-preserving selection process to choose a winning digital component.
* Generating a secret share representing the winning digital component.
* Providing data on whether the application is in the experiment group or control group for each digital component.

==Key Features and Innovation==
* Privacy-preserving cross-domain experiment monitoring.
* Use of secure multi-party computation (MPC) systems.
* Selection process for choosing winning digital components.
* Generation of secret shares for selected digital components.
* Differentiating between experiment and control groups for applications.

==Potential Applications==
This technology can be applied in various fields such as healthcare, finance, marketing, and research where privacy-preserving experiment monitoring is crucial.

==Problems Solved==
This technology addresses the need for monitoring experiments across different domains while maintaining privacy and confidentiality of data.

==Benefits==
* Enhanced privacy protection.
* Secure experiment monitoring.
* Efficient selection process.
* Clear differentiation between experiment and control groups.

==Commercial Applications==
* Healthcare research for monitoring experiments while protecting patient data.
* Marketing studies for analyzing consumer behavior without compromising privacy.
* Financial institutions for conducting experiments on financial products securely.

==Questions about the Technology==
1. How does the privacy-preserving selection process work in this technology?
2. What are the potential implications of using secure multi-party computation systems in experiment monitoring?


==Original Abstract Submitted==

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for privacy-preserving cross-domain experiment monitoring are described. In one aspect, a method includes receiving, by a first server of a MPC system, a request for digital content including a first secret share of an application instance identifier that identifies the application instance associated with the device. The first server conducts, in collaboration with a second server of the secure MPC system, a privacy-preserving selection process to select a winning digital component from a set of digital components. Each digital component has a corresponding unique experiment identifier and unique control identifier. A first secret share representing the winning digital component is generated. A response is generated and includes the first secret share of the selection result and data representing whether the application is in the experiment group or a control group for each digital component.



[[Category:G06F21/62]]
[[Category:G06F21/10]]
[[Category:CPC_G06F21/6245]]