Peer-to-Peer Genetic Data Transfer System
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Solution Overview
Problem
Current methods for data transfer in genetic medical research face challenges in ensuring security and privacy, making it difficult to collect and share large datasets effectively.
Innovation Solution
A peer-to-peer system utilizing cryptographic methods and digital currencies to facilitate secure and private data transfers, where users can encode and share data through a decentralized network, with features like encryption, anonymous transactions, and public ledgers to manage access and permissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional centralized data storage and transfer methods are used, then data accessibility and ease of sharing are improved, but security and privacy protection deteriorate
Solution Approach 1:
The patent segments data into distributed blocks across multiple nodes in a peer-to-peer network, eliminating centralized storage vulnerabilities. Each node holds a portion of the data, making it difficult for any single point of failure or breach to compromise the entire dataset, thus improving both accessibility and security simultaneously.
Solution Approach 2:
The patent introduces cryptographic intermediaries (encryption algorithms, hash functions, and digital signatures) that mediate between data owners and researchers. These cryptographic mechanisms enable secure data sharing without direct exposure of sensitive information, allowing accessibility while maintaining privacy protection through mathematical guarantees rather than trust-based systems.
2Reliability
If data is encrypted and anonymized to protect privacy, then security is improved, but data usability and research validation capability deteriorate
Solution Approach 1:
The patent applies different levels of encryption and anonymization to different portions of data based on sensitivity requirements. Critical personal identifiers receive strong encryption, while research-critical but less sensitive data elements maintain higher usability. This selective approach preserves privacy for sensitive information while maintaining data usability for research purposes.
Solution Approach 2:
The patent performs preliminary data processing including encryption, anonymization, and quality validation before data enters the sharing network. This preliminary action ensures that privacy protection is built-in from the start, and data usability is verified beforehand, preventing loss of information while maintaining security throughout the data lifecycle.
3Reliability
If decentralized peer-to-peer network is implemented, then security and user control are improved, but system complexity and infrastructure requirements deteriorate
Solution Approach 1:
The patent implements a multi-functional platform that combines data sharing, secure messaging, incentive distribution, and research collaboration tools within a single decentralized system. This universality reduces the need for multiple separate systems and infrastructure components, lowering overall complexity while maintaining the security benefits of decentralization through a consolidated protocol layer.
Solution Approach 2:
The patent enables users to independently manage their own data security, access permissions, and incentive rewards through automated smart contracts and cryptographic key management. This self-service capability eliminates the need for complex centralized administrative infrastructure, reducing system complexity while empowering users with direct control over their data and security settings.
4Productivity
If incentives are provided to encourage data sharing, then data collection volume is improved, but system cost and economic complexity deteriorate
Solution Approach 1:
The patent implements a tiered incentive system where users receive rewards proportional to the value and sensitivity of their shared data, rather than uniform payments. This partial action approach allocates resources efficiently by providing stronger incentives only for high-value data contributions, increasing data collection volume while controlling system costs through targeted rather than excessive incentive distribution.
Solution Approach 2:
The patent incorporates automated feedback mechanisms that track data usage, research outcomes, and user contributions, dynamically adjusting incentive distributions based on actual system performance and value creation. This feedback loop ensures that incentive costs are directly tied to productive outcomes, maximizing data collection volume while minimizing wasted economic resources through data-driven optimization.
Data Source
AI summary
A method, system and program product comprise accessing a system having a digital currency infrastructure. At least one user address is created. Genetic and health related user data is prepared. The user data is transferred to the system wherein the system links the user data and the user address.