Anonymous Data Validation via Decentralized Intermediary Network
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Solution Overview
Problem
Online businesses face challenges in validating sensitive information without compromising privacy, as existing solutions require data exchange that may lead to privacy breaches and lack global coverage and reliability, while also being dependent on single sources.
Innovation Solution
A decentralized peer-to-peer private data validation network where members validate data without sharing PII, using encoding and anonymization to ensure privacy and control over their own data, with each member contributing to the network's data validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data exchange is performed for validation, then validation accuracy is improved, but privacy security deteriorates
Solution Approach 1:
A trusted third party platform is introduced as an intermediary to facilitate data validation. The platform receives validation requests from first parties, queries second parties for verification, and returns results without exposing raw PII data. This mediator approach enables accurate validation while maintaining privacy security, as the platform handles the sensitive data exchange process.
Solution Approach 2:
The validation process is segmented into distinct roles: first parties (requesters), second parties (validators), and a trusted third party (platform). Each segment performs specific functions - first parties submit validation requests, second parties verify data accuracy, and the platform coordinates the process. This segmentation allows validation accuracy to be maintained through multiple verification points while privacy is protected by distributing data access across trusted segments rather than centralized exposure.
2Reliability
If PII data is shared for validation, then fraud detection capability is improved, but data security risk worsens
Solution Approach 1:
The trusted third party platform acts as a secure intermediary that enables fraud detection without direct PII sharing between businesses. The platform receives PII data from first parties, validates it against second parties' data, and returns validation results. This intermediary approach maintains fraud detection capability by enabling data comparison while reducing security risks by centralizing data handling with a trusted platform that implements security measures.
Solution Approach 2:
Instead of sharing original PII data between parties, the system uses copies of the data through the trusted third party platform. The platform creates and maintains copies of PII data for validation purposes, allowing fraud detection through comparison while the original data remains secured at each business. This copying approach enables fraud detection capability while minimizing data security risks by avoiding direct data transfer.
3Object-affected harmful factors
If data is kept private, then privacy protection is improved, but validation reliability deteriorates
Solution Approach 1:
The trusted third party platform enables validation reliability to be maintained despite data privacy requirements. The platform receives data from first parties, performs validation by querying second parties, and returns results. This intermediary process ensures validation reliability through systematic verification while maintaining privacy protection by preventing direct data exposure between businesses. The platform's trusted status and controlled data handling processes ensure both reliability and privacy.
Solution Approach 2:
The system implements feedback loops where validation results are returned to first parties through the trusted third party platform. Second parties provide verification feedback on the accuracy of PII data without exposing their raw data. This feedback mechanism maintains validation reliability by confirming data accuracy through multiple sources while preserving privacy protection, as the feedback contains only validation outcomes rather than sensitive data.
Data Source
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AI summary
A system and method for providing anonymous validation of a query among a plurality of nodes in a network: receives at a support node a query from a requester node; wherein the query comprises a one-way function representation of at least one data point of information of the requester node; receives at the support server, from at least one validator node, a one-way function representation of at least one data point of information of the validator node; compares by the support server the query from the requestor node with the one-way function representation of the at least one data point of information; determines by an aggregator server, based on the comparison, whether the at least one data point of information of the requester node matches the at least one data point of information of the at least one validator node; and outputs a match result to the requestor node.