Distributed Hierarchical Database for Biometric Identity Verification
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Solution Overview
Problem
Traditional centralized IT-based solutions for large-scale data management and verification, such as national identification systems, face scalability issues, excessive bandwidth requirements, long retrieval response times, and security vulnerabilities like man-in-the-middle attacks and spoofing, especially in regions with unreliable communications infrastructure.
Innovation Solution
A distributed, hierarchical database system that collects and stores biometric and demographic information based on an individual's mobility history, using client registration devices with internal storage and network interface controllers to ensure secure data handling and caching at local or regional levels, reducing bandwidth needs and enhancing security through unique identification numbers and encryption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized database system is used for large-scale data management, then data verification can be performed, but bandwidth requirements become excessive and retrieval response times become unduly long
Solution Approach 1:
The centralized database is segmented into multiple distributed database nodes deployed across different geographical locations. Each node stores a portion of the personal identification information, allowing verification operations to be distributed across the network rather than funneling all traffic through a single central point, thereby reducing bandwidth requirements and improving response times.
Solution Approach 2:
A hierarchical architecture with intermediate cache servers is introduced between end users and the database nodes. These cache servers store frequently accessed personal identification information locally, acting as intermediaries that fulfill verification requests without requiring constant communication with the central database, thus significantly reducing bandwidth consumption.
2Reliability
If a centralized database system is used for large-scale data management, then data verification can be performed, but retrieval response times become unduly long
Solution Approach 1:
The centralized database is segmented into multiple distributed database nodes deployed across different geographical locations. Each node stores a portion of the personal identification information, allowing verification operations to be distributed across the network rather than funneling all traffic through a single central point, thereby reducing bandwidth requirements and improving response times.
Solution Approach 2:
Personal identification information is pre-loaded into distributed database nodes and cache servers before verification requests arrive. This preliminary distribution of data ensures that when verification requests are made, the data is already positioned close to where it is needed, eliminating retrieval delays associated with fetching data from a distant central database.
3Ease of manufacture
If a centralized database system is used, then data management can be implemented, but security vulnerabilities such as man-in-the-middle attacks, spoofing, and social engineering increase
Solution Approach 1:
The centralized database is segmented into multiple distributed database nodes deployed across different geographical locations. Each node stores a portion of the personal identification information, allowing verification operations to be distributed across the network rather than funneling all traffic through a single central point, thereby reducing bandwidth requirements and improving response times.
Solution Approach 2:
Different database nodes are strategically positioned in different geographical locations to serve different user populations. This local quality approach ensures that verification requests are handled by the nearest appropriate node, reducing latency and bandwidth usage while also distributing security risks across multiple locations rather than concentrating them in a single vulnerable central point.
Data Source
AI summary
A system, method, and client registration and verification device for handling personal identification information. The client device collects from an individual, a sufficient amount of biometric information to uniquely identify the individual, as well as historical mobility information providing a history of locations where the individual has lived. A caching manager stores the collected biometric information at a selected cache node in a hierarchical database having a plurality of cache nodes at multiple levels of the database. The caching manager selects the cache node based on the historical mobility information collected from the individual. The client device sends subsequent requests to verify the identity of the individual to a local cache node where newly input biometric information is compared with the cached information. When the individual's biometric information is not stored in the local cache node, the request is forwarded upward in the database until the cached information is found and compared.


