Confidential Multi-Party Data Processing Through Neutral Mediation
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Solution Overview
Problem
Existing data sharing methods between companies fail to maintain data confidentiality and algorithm secrecy, and secure computation techniques are limited in handling data-dependent branches and require processing rewrites.
Innovation Solution
A processing device and method that acquires and processes data from multiple user terminals, managing data sharing and confidentiality through a neutral third-party system, enabling secure data usage and result sharing without disclosing original data or algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If secure computation is used to keep data encrypted during analysis, then data confidentiality is improved, but algorithm complexity increases and processing rewrites are required
Solution Approach 1:
The patent introduces a neutral third-party processing device as an intermediary between data providers and data users. This mediator performs secure computation by receiving encrypted data from multiple users, processing it without decryption, and returning results. The intermediary handles the complexity of secure computation protocols, allowing original users to avoid implementing complex secure computation themselves while maintaining data confidentiality throughout the process.
2Adaptability or versatility
If data is shared between companies for analysis, then data utilization is improved, but data security deteriorates
Solution Approach 1:
The patent segments the data sharing process into distinct functional components: data input from multiple users, encrypted processing by a neutral third party, and result distribution. Each user's data remains isolated and encrypted throughout the process, with only aggregated results being shared back. This segmentation allows broad data utilization across multiple companies while maintaining individual data security through cryptographic isolation.
3Reliability
If proprietary algorithms are kept secret, then corporate confidentiality is improved, but collaboration capability deteriorates
Solution Approach 1:
The neutral third-party processing device serves as an intermediary that enables collaboration without requiring parties to reveal their proprietary algorithms. Each company inputs their data and algorithmic requirements to the mediator, which performs the computation using secure multi-party computation techniques. The mediator returns results without exposing any party's algorithms to others, thus maintaining corporate confidentiality while enabling collaborative data analysis that would otherwise require direct algorithm sharing.
Data Source
AI summary
A processing device includes: an acquiring unit which acquires first processing data from a first user terminal and acquires second processing data from a second user terminal; a matching unit which receives a request for sharing result data of processing by the first processing data and the second processing data from the first user terminal and receives permission of use of the second processing data by the first user terminal from the second user terminal; a processing unit which, when receiving permission from the second user terminal, processes the first processing data and the second processing data and outputs result data; and a providing unit which provides the result data to the first user terminal.