Composite MPC Requests for Low-Latency Secure Component Selection
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Solution Overview
Problem
Existing secure multi-party computation (MPC) systems face challenges in efficiently selecting digital components for display on client devices while preserving user privacy and security, particularly in reducing latency, bandwidth consumption, and computational requirements.
Innovation Solution
A secure MPC protocol involving multiple MPC computers collaboratively select digital components using secret shares and probabilistic data structures, reducing data transmission and computations by leveraging results across digital component slots, and ensuring user information is not accessed in cleartext without collusion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If secure MPC protocols are used to select digital components while preserving user privacy, then user information security is improved, but computational requirements and latency increase
Solution Approach 1:
The system performs preliminary actions by pre-computing and caching selection results for digital components based on user profiles and component characteristics. When a request arrives, the MPC protocol validates against pre-computed results rather than performing full computations, significantly reducing latency while maintaining security guarantees.
Solution Approach 2:
The MPC computation is segmented into multiple independent steps: profile matching, component filtering, selection criteria evaluation, and final selection. Each segment can be processed separately and cached, allowing parallel execution and reducing overall computational burden while preserving privacy through distributed computation across multiple parties.
2Reliability
If secure MPC protocols are used to select digital components while preserving user privacy, then user information security is improved, but bandwidth consumption increases
Solution Approach 1:
The system extracts only the essential elements needed for secure comparison from user profiles and digital component data. Instead of transmitting complete datasets, only critical features and selection criteria are exchanged between MPC parties, minimizing bandwidth consumption while maintaining the ability to perform secure multi-party computation for accurate selection.
3Measurement precision
If traditional MPC systems select digital components for each slot independently, then selection accuracy is improved, but latency and computational requirements worsen
Solution Approach 1:
The system merges the selection process across multiple digital component slots by identifying common user profile matches and component eligibility criteria that apply to multiple slots. Once a user profile matches certain criteria for one slot, the same matching logic is reused for other slots, reducing redundant computations and latency while maintaining accurate selection for each individual slot based on its specific requirements.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using cryptographic techniques to enhance data security and privacy and increasing computational efficiency in selecting digital components for multiple digital component slots are described. In one aspect, a method includes receiving, from a client device and by a first MPC computer of a group of MPC computers that collaborate to perform MPC computations, a composite request for digital components to display in multiple digital component slots of an electronic resource. The composite request includes first secret shares of data identifying user groups that include a user of the client device as a member. A determination is made, in collaboration with one or more second MPC computers, a first secret share of a value of each of multiple candidate parameters of a candidate expression for each digital component in a set of digital components.