Secure MPC Location-Based Content Selection Without Cleartext Exposure
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Solution Overview
Problem
Existing secure multi-party computation (MPC) systems fail to protect user privacy and security by allowing access to sensitive location information and user data in cleartext, leading to potential micro-targeting and user profiling.
Innovation Solution
Implementing a secure MPC protocol using secret shares and attestation tokens to distribute digital components based on user location and group membership, ensuring that no single party can access user data in cleartext, and using probabilistic data structures to reduce data size and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If secure MPC protocols are used to protect user privacy by distributing computations across multiple parties, then user information security is improved, but computation speed and system complexity increase
Solution Approach 1:
The patent divides user information into secret shares distributed across multiple MPC computers (e.g., first secret share to first computer, second secret share to second computer). No single computer holds the complete information, ensuring security while enabling collaborative computation. This segmentation resolves the contradiction by structuring the system to inherently protect privacy without requiring complex additional security layers.
Solution Approach 2:
The patent introduces attestation tokens as intermediaries that verify device integrity and authenticate participants in the MPC protocol. These tokens mediate between security requirements and computation efficiency by providing verified trust signals, allowing the system to proceed with computations only when integrity is confirmed, thus balancing security and performance.
2Reliability
If secure MPC protocols are used to prevent unauthorized access to sensitive user information, then privacy protection is improved, but computation time increases
Solution Approach 1:
The patent performs integrity verification and attestation token validation before the main MPC computations begin. By preparing and verifying trust signals in advance, the system ensures security requirements are met upfront, allowing the subsequent secret share computations to proceed efficiently without repeated security checks during the computation process.
Solution Approach 2:
The patent replaces traditional cryptographic verification mechanisms with attestation token-based verification. This substitution uses hardware-enforced trust signals and structured attestation protocols that are more efficient than conventional cryptographic proof systems, reducing computation time while maintaining strong privacy protection guarantees.
3Reliability
If secret shares are distributed across multiple parties for secure computation, then data security is improved, but communication bandwidth consumption increases
Solution Approach 1:
The patent extracts and processes only the essential secret share data required for the specific computation task, rather than transmitting complete datasets. By extracting only the necessary portions of secret shares and processing them locally at each MPC computer, the system reduces communication overhead while maintaining data security through the distributed secret share architecture.
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 increase computational efficiency in selecting digital components are described. In one aspect, a method includes receiving, by an MPC computer of a group of MPC computers configured to perform computations of a secure MPC protocol to select digital components for distribution to client devices, a first secret share of location information indicating a location of a client device. The MPC computer generates, by performing the computations of the secure MPC protocol in collaboration with one or more second computers of the group of MPC computers, a first secret share of a selection result including data identifying a selected digital component that is selected from candidate digital components that are candidates based at least in part on the location of the client device.