View source for 17928714. PRIVACY-PRESERVING AND SECURE APPLICATION INSTALL ATTRIBUTION simplified abstract (Google LLC)

=PRIVACY-PRESERVING AND SECURE APPLICATION INSTALL ATTRIBUTION=


==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:Nicholas Alexander Bruno Sabatino of San Francisco CA (US)|Nicholas Alexander Bruno Sabatino of San Francisco CA (US)]][[Category:Nicholas Alexander Bruno Sabatino of San Francisco CA (US)]]

[[:Category:Alex Daniel Jacobson of Mountain View CA (US)|Alex Daniel Jacobson of Mountain View CA (US)]][[Category:Alex Daniel Jacobson of Mountain View CA (US)]]

==PRIVACY-PRESERVING AND SECURE APPLICATION INSTALL ATTRIBUTION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17928714 titled 'PRIVACY-PRESERVING AND SECURE APPLICATION INSTALL ATTRIBUTION

==Simplified Explanation==

The patent application describes methods, systems, and apparatus for securely attributing application installations while preserving user privacy. 

* Detection of user interaction with a digital component initiating installation of a software application.
* Installation of the software application at a client device.
* Obtaining impression data and interaction data referencing the software application.
* Assigning attribution credits for the installation by applying an attribution model to the data.
* Generating attribution tokens containing data identifying the software application, the attribution credit, and an integrity token.

== Potential Applications ==
This technology could be applied in the fields of digital marketing, app development, and user analytics.

== Problems Solved ==
This technology addresses the challenge of accurately attributing app installations to specific interactions or impressions while maintaining user privacy.

== Benefits ==
The benefits of this technology include improved accuracy in attributing app installations, enhanced user privacy protection, and better insights into user behavior.

== Potential Commercial Applications ==
*Enhanced Attribution Model for App Installations*

== Possible Prior Art ==
There may be prior art related to attribution models for digital interactions and installations, but specific examples are not provided in the patent application.

== Unanswered Questions ==

=== How does this technology impact user experience with app installations? ===
This article does not delve into the potential effects of this technology on the user experience during app installations. 

=== What are the potential limitations of this attribution model in real-world scenarios? ===
The patent application does not discuss any potential drawbacks or limitations of the described attribution model.


==Original Abstract Submitted==

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for securely attributing application (app) installations while preserving user privacy are described. In one aspect, a method includes a given digital component that can be provided and can include a reference to a software application. A user interaction with the digital component that initiates installation of the application can be detected. The software application can be installed at a client device. The following can be obtained: (i) impression data that reference the software application and (ii) interaction data that reference the software application. Attribution credits for the installation of the software application can be assigned by applying an attribution model to the presentation and interaction data. Attribution tokens can be generated that includes (i) data identifying the software application, (ii) data identifying the respective attribution credit assigned to the entity, and (iii) and an integrity token.



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