Secure Multi-Party Computation for Private Data Matching

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Solution Overview

Problem

Conventional approaches for multi-party computations require a trusted third party to facilitate data collaboration, which raises concerns about data secrecy and compliance with data retention policies, and lacks assurance that sensitive data will not be abused or accessed unauthorized.

Innovation Solution

Implementing secure multi-party computation (MPC) techniques that allow parties to jointly perform analyses on their datasets without revealing sensitive information, using shared universal identifiers to map and match vectors between datasets, enabling secure lift analysis and other computations without a trusted intermediary.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If entities use a trusted third party to facilitate data collaboration, then data joining and analysis can be performed, but data secrecy and compliance with retention policies are compromised

Engineering Contradiction:

Improveease of data collaborationVSAvoiddata secrecy

Core Design Contradiction:

Ease of manufactureVSReliability

Solution Approach 1:

The patent uses secure multi-party computation protocols as an intermediary mechanism that enables data collaboration without requiring entities to directly share sensitive data. The computation is performed on encrypted data, with only results revealed, thus maintaining data secrecy while enabling collaboration.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent creates encrypted copies of data for computation purposes. Entities provide encrypted versions of their data to the computation system, which processes these copies without accessing the original sensitive information, thereby preserving data secrecy while enabling analysis.

Inventive Principle:

Principle #26Copying

2Productivity

If entities share sensitive data with a third party for analysis, then collaborative insights can be gained, but unauthorized access and data abuse risks increase

Engineering Contradiction:

Improvecollaborative insight generationVSAvoidunauthorized access risk

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The patent changes the state of data from plaintext to encrypted form before sharing. By transforming data parameters (encryption state), the system enables collaborative analysis while preventing unauthorized access, as the data remains unintelligible without proper decryption keys.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent converts the potential harm of data sharing into benefit by using encryption. The very act of obscuring data through encryption, which might seem to hinder analysis, actually enables secure collaboration by preventing unauthorized access while still allowing legitimate analysis on encrypted data.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

3Ease of operation

If entities rely on third-party data management, then data processing can be facilitated, but compliance with data retention policies cannot be assured

Engineering Contradiction:

Improvedata processing facilitationVSAvoiddata retention control

Core Design Contradiction:

Ease of operationVSLoss of information

Solution Approach 1:

The patent segments the data processing function into multiple independent components: data input, encryption, computation execution, and result output. Each entity maintains control over their own data segment, while the system coordinates processing, ensuring retention policies are maintained through distributed control rather than centralized third-party management.

Inventive Principle:

Principle #1Segmentation

4Productivity

If sensitive data is provided to a trusted third party, then lift analysis can be performed, but data privacy and confidentiality are compromised

Engineering Contradiction:

Improvelift analysis capabilityVSAvoiddata confidentiality

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The patent replaces the mechanical system of physical data transfer and manual trust verification with cryptographic mechanisms. Secure multi-party computation protocols automatically enforce confidentiality through mathematical guarantees, eliminating the need for trust-based relationships while enabling lift analysis.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11593510B1Systems and methods for securely sharing and processing data between parties

Publication Date: 2023.02.28 META PLATFORMS INC

AI summary

Systems, methods, and non-transitory computer-readable media can determine a first dataset provided by a first party, wherein the first dataset includes a set of vectors that are each associated with a user identifier. A second dataset provided by a second party can be determined, wherein the second dataset includes a set of vectors that are each associated with a user identifier. One or more vectors in the first dataset can be matched to vectors in the second dataset based on a secure multi-party computation without revealing respective graph information of the first party or the second party. Respective mappings between vectors in the first dataset to a set of shared universal identifiers can be provided to the first party. Respective mappings between vectors in the second dataset to the set of shared universal identifiers can be provided to the second party.