Intelligent Health Blockchain for Secure Data Storage
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Solution Overview
Problem
Existing blockchain systems for storing health data require significant computational resources and are vulnerable to fraudulent activities due to infrequent data transmission, which increases the risk of data compromise before it is stored on the blockchain.
Innovation Solution
A dynamic system for generating an intelligent health-based blockchain that periodically updates user health data by retrieving and comparing hash values from network nodes, generating new block instances using a hashing algorithm, and storing data in volatile memory to reduce computational burden and enhance security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If health data is transmitted frequently to the blockchain, then data security is improved by reducing the window for fraudulent activity, but computational power requirements increase
Solution Approach 1:
The system performs preliminary actions by collecting and validating health data locally before blockchain submission. The health-tracking device continuously monitors and stores data in local memory, preparing it for periodic blockchain updates. This preliminary local processing reduces the frequency of blockchain write operations while maintaining data security, as data is already secured in transit-ready format when submitted.
Solution Approach 2:
Instead of continuous real-time blockchain updates, the system implements periodic batch submissions of health data. The blockchain is updated at predetermined intervals with aggregated data sets, reducing the computational burden on network nodes while maintaining adequate security. The periodic nature allows for efficient resource utilization without sacrificing the integrity of health records.
2Productivity
If health data is transmitted less frequently to reduce computational burden, then processing power requirements decrease, but the risk of fraudulent activity increases
Solution Approach 1:
The system incorporates feedback mechanisms where blockchain network nodes validate incoming health data against previously stored records and cryptographic signatures. Each blockchain update includes verification data that provides feedback on data integrity, allowing the system to maintain fraud resistance even with periodic updates. The feedback loop ensures that any attempted fraudulent modifications are detected and rejected.
Solution Approach 2:
The patent introduces cryptographic intermediaries including digital signatures, hash functions, and encryption protocols that mediate between the health-tracking device and blockchain network. These cryptographic intermediaries secure data transmission and storage without requiring frequent blockchain interactions, thereby maintaining fraud resistance while reducing processing requirements. The intermediary cryptographic layer verifies data authenticity without demanding continuous computational resources.
3Loss of information
If multiple batches of health data are processed continuously, then data completeness is improved, but system complexity increases
Solution Approach 1:
The system merges multiple batches of health data into consolidated blocks before blockchain submission. Instead of processing each data batch separately, the health-tracking device aggregates data over time and submits combined data sets to the blockchain. This merging approach ensures complete health records are captured while significantly reducing the number of blockchain write operations and simplifying system architecture.
Solution Approach 2:
The blockchain data structure is segmented into discrete blocks with clear boundaries and organizational structures. Each block contains specific health data sets with embedded metadata for tracking and verification. This segmentation allows the system to manage data completeness efficiently by organizing information into manageable units that can be processed and validated systematically without overwhelming system complexity.
Data Source
AI summary
A computer implemented method for safe, efficient, and fraud-proof continuous retrieval of health data is disclosed. The method comprises receiving a request to update a record associated with a user blockchain comprising identification information associated with a health tracker, a health tracker server, and user authentication data; generating an instruction to receive user data based on the identification information and user authentication data; receiving health data from the health tracker server; retrieving and verifying the validity of the user's latest blockchain; storing the data in a volatile memory; and creating a new block instance corresponding to the data.