Decentralized Database Event Authorization via Hashed Identifiers
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Solution Overview
Problem
Centralized databases face issues such as single points of failure, dependency on network connectivity, limited access to data, and inadequate protection of user privacy, leading to inefficiencies and security concerns.
Innovation Solution
A decentralized database system using blockchain technology, where events are managed by incorporating identifiers like hashed values of event counters to authorize access and ensure privacy, allowing only authorized users to access confidential events through a peer-to-peer network and smart contracts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a centralized database is used to store and maintain data in one single location, then ease of management and control is improved, but reliability deteriorates due to single point of failure
Solution Approach 1:
The patent divides the centralized database into multiple distributed nodes across a peer-to-peer network. Each node maintains copies of data, eliminating the single point of failure while preserving management capabilities through distributed consensus mechanisms.
Solution Approach 2:
The patent creates multiple copies of data across different nodes in the distributed network. These replicas ensure that data remains accessible even if one node fails, thereby improving reliability while maintaining ease of management through automated replication.
2Loss of information
If a centralized database maintains a single copy of data, then data redundancy is minimized, but loss of information worsens when data is unexpectedly lost
Solution Approach 1:
The patent implements multiple copies of data across distributed nodes. When data is lost from one node, identical or redundant copies from other nodes can be retrieved, preventing information loss while maintaining efficient storage through selective replication.
Solution Approach 2:
The patent changes the storage parameter from single-copy centralized to multi-copy distributed. This transformation allows the system to tolerate data loss at individual nodes while maintaining overall data availability through the network.
3Ease of operation
If a centralized database experiences high traffic, then service concentration is improved, but productivity deteriorates due to bottlenecks
Solution Approach 1:
The patent segments the centralized processing load across multiple distributed nodes. Each node can independently handle database operations, eliminating bottlenecks and increasing overall processing capacity while maintaining service concentration through coordinated access.
4Ease of operation
If a centralized database requires network connectivity for access, then ease of operation is improved for remote access, but reliability worsens when network connection is slow or interrupted
Solution Approach 1:
The patent places data copies at multiple network locations, allowing users to access data from the nearest or most available node. This reduces network dependency and maintains access availability even when specific network connections are slow or interrupted.
Data Source
AI summary
An example operation may include one or more of receiving an event from a node, extracting an identifier from the event, determining whether the event is authorized, and generating a notification of the event when the identifier is authorized, wherein the identifier includes a hashed value of an event counter and wherein the identifier is authorized when the hashed value matches a hashed value of the event counter stored in a storage area of or coupled to the client.