Risk Assessment Visualization Using Self-Organizing Map
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Combining multiple model predictions from different data sources for effective risk assessment in access control is challenging, especially as the number of scores grows, making it difficult to determine which user devices to approve or decline access in online interactive computing environments.
Innovation Solution
A computer-implemented method and system that generates a classification map by grouping entities based on risk assessment data from multiple sources, using a self-organizing map (SOM) model to visualize and edit risk assessments, allowing for intuitive decision-making through a user interface with selectable editing tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple model predictions from different data sources are combined for risk assessment, then the accuracy and comprehensiveness of risk evaluation is improved, but the complexity of the decision-making process increases
Solution Approach 1:
The patent combines multiple risk scores from different data sources (user profile, device behavior, third-party assessments, online activity) into a unified risk assessment visualization. The self-organizing map integrates these multiple predictions by mapping them to a two-dimensional space where similar risk profiles are grouped together, allowing decision-makers to view combined risk information in a single coherent interface rather than separately analyzing multiple scores.
Solution Approach 2:
The patent transforms high-dimensional risk assessment data from multiple sources into a two-dimensional self-organizing map visualization. This dimensionality reduction technique projects complex multi-source risk scores onto a 2D grid where the position of each entity is determined by its risk profile characteristics, making it easier to visualize and compare multiple risk dimensions simultaneously without being overwhelmed by the number of input parameters.
2Reliability
If multiple risk scores from different data sources are integrated, then the effectiveness of access control strategy is improved, but the time and effort required for decision-making increases
Solution Approach 1:
The system pre-processes and organizes multiple risk scores into a self-organizing map structure before the actual access control decision is needed. By pre-grouping entities with similar risk profiles and pre-calculating their positions in the 2D space, the system eliminates the need for time-consuming analysis of multiple data sources at the moment of decision-making. Users can quickly reference the pre-organized visualization to make rapid access control decisions based on already-integrated risk information.
3Measurement precision
If risk assessment data from multiple data sources is processed, then the quality of risk evaluation is improved, but the difficulty of visualizing and editing the data increases
Solution Approach 1:
The patent reduces the complexity of visualizing multi-source risk data by projecting it onto a two-dimensional self-organizing map. This transformation allows users to visually navigate and interact with complex risk assessment data from multiple sources (user profile, device behavior, third-party assessments, online activity) through an intuitive 2D interface, where entities with similar risk profiles are spatially grouped, making both visualization and editing operations much more manageable than working with raw multi-dimensional data tables.
Data Source
AI summary
In some embodiments, a data visualization system accesses data entries associated with entities and obtained from multiple data sources. The data visualization system generates a classification map for the entities by classifying the entities into groups based on the data entries from the multiple data sources. The groups are arranged in the classification map according to values of the data entries of the entities. The data visualization system determines one or more metrics for the groups. The data visualization system further determines visualizations based on the classification map, each visualization representing a metric or the data entries from one of the data sources. The data visualization system generates, for inclusion in a user interface of the system, selectable interface elements configured for invoking an editing tool for updating the visualizations. The selectable interface elements for the visualizations are arranged in the respective visualizations according to the classification map.