Hybrid Data-Source Verification for Real-Time Sensitive Records
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Solution Overview
Problem
Sensitive data stored in online repositories often change frequently and are difficult to access due to strict access controls, leading to inaccuracies and delays in electronic transactions.
Innovation Solution
A verification computing system uses a hybrid data source approach, combining an internal verification repository with external-source caches to service verification queries in real-time by querying both sources, consolidating data records, and maintaining security through hashed identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensitive data is stored in a secured manner to prevent unauthorized access, then data security is improved, but access speed and transaction completion time deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-fetching and caching sensitive data from external sources before verification queries are submitted. The cache is proactively updated with entity data, so when a verification query arrives, the data is already available locally, eliminating the need for time-consuming real-time external access while maintaining security through controlled cache management.
Solution Approach 2:
The verification cache acts as an intermediary layer between the secure internal verification repository and external data sources. It stores pre-retrieved sensitive data locally, allowing fast access without directly querying external sources during verification. This intermediary cache resolves the contradiction by providing quick access to sensitive data while maintaining security through its controlled architecture.
2Reliability
If strict access control requirements are implemented for sensitive data, then data security is improved, but data accuracy maintenance effort increases
Solution Approach 1:
The system implements self-service by automatically updating the verification cache with fresh data from external sources based on cached timestamps and data age criteria. When data in the cache approaches its age threshold, the system autonomously re-fetches updated data without manual intervention, maintaining data accuracy while reducing the operational complexity of manual data updates.
Solution Approach 2:
The system employs periodic action by scheduling automatic cache updates at predetermined intervals based on data age thresholds. Instead of continuous monitoring or manual updates, the cache is periodically refreshed when entities indicate data changes or when cached data reaches its age limit, simplifying maintenance while ensuring data remains current.
3Measurement precision
If real-time verification of sensitive data is performed by querying external sources, then data accuracy is improved, but network bandwidth consumption increases
Solution Approach 1:
The system extracts only the essential verification data needed for specific entities from external sources and stores it locally in the cache. When verification queries are received, the system checks the cache first and serves data from local storage without querying external sources, thereby extracting and retaining only the necessary information locally to avoid repeated network transmissions.
Solution Approach 2:
The system implements local quality by maintaining a localized verification cache with pre-retrieved sensitive data for specific entities. Instead of uniformly querying external sources for every verification request, the system serves data from the local cache when available, providing fast accurate verification for cached entities while reducing network bandwidth consumption by avoiding redundant external queries.
Data Source
AI summary
In some aspects, a verification system can receive a verification query from a verifier computing system for requesting verification of characteristics of an entity involved in an online interaction. The verification query can include a unique identifier (“UID”) of the entity. The verification computing system can query a verification repository in the verification computing system based on the UID. Additionally, the verification computing system can query an external-source cache using the UID. In response to determine a match for the UID in the external-source cache, the verification computing system can request external sensitive data records for the entity from an external source corresponding to the external-source cache. Generating consolidated sensitive data records can involve consolidating the external sensitive data records and internal sensitive data records obtained through querying the verification repository. A verification result, generated using the consolidated sensitive data records, can be transmitted to the verifier computing system.