Network Risk Hierarchy for Relative Assessment and Control Coverage
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Integrating data from separate systems in a network is challenging due to format differences, requiring significant computing power and technical complexity, and it's difficult to analyze large amounts of risk data with unclear relative risk and varying levels of detail, making it hard to monitor changes and mitigate risks effectively.
Innovation Solution
A system that aggregates risk factors into a hierarchy of groupings, determines risk assessments using risk data and controls, and outputs these assessments on a user interface, reducing computing power requirements and enhancing risk management capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data from separate network systems is integrated through traditional methods, then comprehensive risk assessment can be achieved, but the process requires significant computing power and time
Solution Approach 1:
The patent segments the risk assessment process by organizing risk factors into a hierarchy of groupings (e.g., risk categories, subcategories, individual risk factors). This segmentation allows the system to process and assess risks at multiple levels simultaneously, reducing the computational burden compared to analyzing all risk factors in a single integrated process. Each grouping can be assessed independently and then aggregated.
Solution Approach 2:
The patent introduces a hierarchical dimension to the risk assessment process, organizing risk factors into multiple levels (categories, subcategories, individual factors). This dimensional organization transforms the flat, computationally intensive integration problem into a structured, multi-level assessment that reduces computing requirements by processing risks at appropriate granularities.
2Reliability
If data from separate network systems is integrated through traditional methods, then comprehensive risk assessment can be achieved, but the process takes significant time
Solution Approach 1:
By segmenting risk factors into hierarchical groupings, the system can perform parallel processing at different levels of the hierarchy. This segmentation enables the assessment to be completed more quickly compared to sequential processing of all risk factors individually.
Solution Approach 2:
The patent establishes predefined associations between risk factors and risk controls, and organizes risk factors into hierarchical groupings in advance. This preliminary structuring eliminates the need for complex real-time data integration and analysis, significantly reducing the time required to perform risk assessments.
3Measurement precision
If detailed analysis of individual risk factors is performed separately, then precise risk assessment can be achieved, but computational requirements increase
Solution Approach 1:
The patent segments the analysis into hierarchical levels, allowing precise assessment of individual risk factors while organizing them into manageable groups. This segmentation maintains measurement precision at the individual factor level while reducing system complexity through structured organization.
Solution Approach 2:
By adding the hierarchical dimension to risk factor organization, the system achieves precise measurement of individual risks without increasing overall complexity. The hierarchical structure provides a natural framework for organizing detailed analysis results.
Data Source
AI summary
Relative risk in a network system can be determined according to some examples. For example, a computing system can determine a hierarchy of groupings for risk factors within a network based on risk data associated with the risk factors. The computing system can determine associations between the risk data and the risk controls. Each risk control can represent an amount of control for reducing riskiness of a risk factor. The computing system can determine a risk assessment for each grouping of the hierarchy of groupings based on the risk data, the risk controls, and the hierarchy of groupings. Determining the risk assessment can include determining a control coverage for each grouping based on the associations and the risk data. The computing system can output the risk assessment for each grouping of the hierarchy of groupings for display on a graphical user interface.