Homomorphic Encryption for Secure Data Comparison
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Solution Overview
Problem
There is a need for a method to securely share proprietary data between two parties in a transaction without revealing sensitive information, allowing each party to decide whether to proceed without compromising their data.
Innovation Solution
The method employs asymmetric secure comparison using homomorphic encryption and public-private key paradigms, enabling parties to compare information such as molecular structures or bids without disclosing their actual data, by exchanging encrypted and scrambled fingerprints, and determining similarity or identity through secure computation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parties share proprietary data directly to enable comparison and decision-making, then transaction efficiency is improved, but data confidentiality and security are compromised
Solution Approach 1:
The patent introduces encrypted fingerprints as an intermediary representation of proprietary data. Instead of sharing raw molecular structures or bids, parties convert their data into encrypted fingerprints that preserve essential comparison capabilities while preventing direct access to the underlying proprietary information. This intermediary form enables secure comparison and transaction decisions without compromising data confidentiality.
2Loss of information
If parties use encrypted data comparison methods, then data confidentiality is maintained, but computational complexity and processing time increase
Solution Approach 1:
The patent extracts only the essential features needed for comparison by converting proprietary data into fingerprints. This extraction process removes unnecessary computational overhead while retaining the critical information required for meaningful comparison. The fingerprint representation captures the essential characteristics of molecules or bids in a condensed form that is both secure and computationally efficient to process.
3Measurement precision
If parties exchange detailed information to make informed decisions, then decision quality is improved, but the risk of information leakage and competitive disadvantage increases
Solution Approach 1:
The patent applies local quality by providing different levels of information disclosure to different parties based on their needs and trust levels. Each party receives encrypted fingerprints that contain precisely the information needed for comparison decisions, no more and no less. This localized information provision ensures decision quality while minimizing unnecessary information exposure that could lead to competitive disadvantages.
Data Source
AI summary
The technology encompasses new uses of already-known cryptographic techniques. The technology entails computer-based methods of sharing information securely, in particular an asymmetric method of secure computation that relies on the private-key/public key paradigm with homomorphic encryption. The methods and programmed computing apparatuses herein apply mathematical concepts to services or tasks that are commercially useful and that have not hitherto been possible. Applications of the methods within cloud computing paradigms are presented. Applications of the methods and apparatus herein are far-ranging and include, but are not limited to: purchase-sale transactions such as real estate or automobiles, where some aspect of price negotiation is expected; stock markets; legal settlements; salary negotiation; auctions, and other types of complex financial transactions.