Entity Identification Normalization for Access Control
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Solution Overview
Problem
Existing information systems face challenges in efficiently controlling interactions and preventing unauthorized access, particularly in identifying and managing clients engaged in restricted activities across diverse geographic and virtual locations, while ensuring compliance with regulations.
Innovation Solution
A computing platform that performs iterative fuzzy searches and comparisons of multiple variables to normalize entity identification information and interaction records, determining interaction scores, and sending alerts to control servers to block or allow interactions based on these scores, thereby managing access and compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional exact matching methods are used to identify clients, then precision in identifying restricted entities is improved, but the system cannot handle variations in entity identification formats and data quality, reducing adaptability
Solution Approach 1:
The patent applies parameter changes by transforming entity identification data through normalization processes that adjust data formats, quality levels, and representation parameters. The system changes the state of identification data from raw heterogeneous formats to normalized comparable formats, enabling both precision and adaptability in identifying restricted entities across different data sources and formats
Solution Approach 2:
The patent introduces an intermediary normalization layer between raw entity identification data and the matching process. This intermediary component transforms diverse identification formats into a common normalized format, serving as a mediator that enables precise comparison while accommodating various input formats and data quality levels
2Reliability
If comprehensive client verification is performed to ensure compliance, then security is improved, but the processing time and system complexity increase
Solution Approach 1:
The patent applies preliminary action by performing normalization and preliminary matching operations before final compliance verification. The system prepares identification data in advance through normalization and conducts initial similarity assessments, so that when compliance verification is needed, the processing time is reduced because foundational work has already been completed
Solution Approach 2:
The patent implements partial action by using similarity scoring that can identify restricted entities with high confidence without requiring complete verification of all possible attributes. The system performs sufficient verification to achieve compliance reliability while avoiding unnecessary processing of all potential matching criteria, thus reducing verification time
3Adaptability or versatility
If multiple identification formats are supported to accommodate diverse clients, then adaptability is improved, but data normalization and comparison complexity increase
Solution Approach 1:
The patent applies universality by creating a universal normalization framework that handles multiple entity identification formats through a single unified process. The normalization component serves multiple functions: format conversion, quality assessment, and standardization, all within one systematic approach that accommodates diverse client data without requiring separate processing paths for each format
Data Source
AI summary
A computing platform may receive, from a web server, entity identification information in different formats, and normalize the entity identification information. After normalizing the information, the computing platform may receive a plurality of interaction records each associated with an interaction between a system and a client of the system. The computing platform may compare the normalized entity identification information with the interaction records of the interactions between the system and the clients of the system. After determining that the entity identification information matches client information for one of the interaction records, the computing platform may send an alert to a control server. The alert may cause the control server to take one or more actions with respect to the client. For example, future attempts by the client to access one or more services offered by the system may be blocked for access by the client.