Google llc (20240232423). PRIVACY-PRESERVING CROSS-DOMAIN EXPERIMENTAL GROUP PARTITIONING AND MONITORING simplified abstract
Contents
PRIVACY-PRESERVING CROSS-DOMAIN EXPERIMENTAL GROUP PARTITIONING AND MONITORING
Organization Name
Inventor(s)
Gang Wang of Frederick MD (US)
Marcel M. Moti Yung of New York NY (US)
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 20240232423 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.
- The method involves receiving a request for digital content with a secret share of an application instance identifier.
- A privacy-preserving selection process is conducted to choose a winning digital component from a set of components.
- Secret shares representing the winning component are generated, along with data indicating if the application is in an experiment group or control group for each component.
Key Features and Innovation:
- Utilizes secure multi-party computation systems for privacy-preserving experiment monitoring.
- Involves a selection process to choose digital components while maintaining privacy.
- Generates secret shares to represent the winning digital component and the application's group assignment.
Potential Applications:
- Research institutions for conducting experiments while protecting sensitive data.
- E-commerce platforms for A/B testing without revealing individual user information.
- Healthcare organizations for analyzing patient data across different domains securely.
Problems Solved:
- Protects privacy in cross-domain experiment monitoring.
- Enables collaboration on data analysis without sharing sensitive information.
- Facilitates secure selection processes for digital components in experiments.
Benefits:
- Enhanced privacy protection for sensitive data.
- Secure collaboration on experiments across different domains.
- Efficient selection processes for digital components without compromising privacy.
Commercial Applications: Secure Multi-Party Computation for Privacy-Preserving Experiment Monitoring: Market Implications and Potential Uses
Questions about Secure Multi-Party Computation for Privacy-Preserving Experiment Monitoring: 1. How does secure multi-party computation ensure privacy in cross-domain experiment monitoring? 2. What are the key benefits of using secure multi-party computation systems for 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.
