Dynamic Risk Score Calculation for Network Vulnerability Prioritization
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Solution Overview
Problem
Vulnerability assessment systems in managed networks generate overwhelming amounts of data, making it difficult for security managers to prioritize and address identified vulnerabilities due to the inability to combine vulnerability severity with device importance for an overall risk score.
Innovation Solution
A risk scoring system that calculates a weighted average of vulnerability severity and device importance, allowing security managers to dynamically adjust factors and weights, with a graphical user interface displaying a manageable subset of risk score combinations to facilitate decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vulnerability assessment systems identify all vulnerabilities in a managed network, then the completeness of vulnerability detection is improved, but the complexity of data management and analysis increases
Solution Approach 1:
The patent segments the overwhelming vulnerability data by introducing a risk score that divides vulnerabilities into distinct priority levels (e.g., critical, high, medium, low). This segmentation allows security managers to focus on specific subsets of vulnerabilities based on their risk level, rather than managing all vulnerabilities uniformly. The system calculates risk scores by combining vulnerability severity with device importance metrics, creating manageable categories that reduce data complexity.
Solution Approach 2:
The patent introduces an intermediary mechanism - the risk score calculation system - that acts as a mediator between raw vulnerability data and security manager decision-making. This intermediary process automatically combines multiple factors (vulnerability severity, device importance, exposure level) into a single synthesized risk score, reducing the cognitive load on security managers while maintaining comprehensive vulnerability assessment.
2Measurement precision
If vulnerability assessment systems provide detailed information about each vulnerability, then the accuracy of security assessment is improved, but the ease of operation deteriorates
Solution Approach 1:
The patent transforms multiple complex parameters (vulnerability severity, device importance, exposure level) into a single simplified parameter - the risk score. This parameter change allows security managers to assess and prioritize vulnerabilities using one straightforward metric rather than analyzing multiple detailed factors simultaneously, significantly improving ease of operation while preserving the accuracy benefits of comprehensive assessment.
Solution Approach 2:
The patent merges multiple assessment dimensions (vulnerability characteristics and device characteristics) into a unified risk score. By combining vulnerability severity with device importance metrics in a weighted calculation, the system creates a single comprehensive indicator that maintains the accuracy of detailed assessment while presenting a simplified view for operational decision-making.
3Measurement precision
If multiple factors are used to calculate risk scores, then the accuracy of risk representation is improved, but the complexity of factor combinations increases
Solution Approach 1:
The patent introduces dynamic adjustability in the risk scoring system, allowing security managers to modify the weights assigned to different factors based on their specific organizational needs and threat landscapes. This dynamic capability enables the system to maintain accurate risk representation across different contexts while managing complexity through flexible, adaptable configurations rather than fixed rigid structures.
Data Source
AI summary
A system may include a server device configured to: receive selected factors and respective weights for each of the selected factors; obtain combinations of selected primary factors that total less than a maximum number of rows; determine a duplication count for the combinations of selected primary factors; and generate, for display on a graphical user interface, data representing a table, where each column of the table represents one of the selected factors, where for columns of the table representing selected primary factors, rows represent each of the combinations of selected primary factors duplicated according to the duplication count, where for columns of the table representing selected secondary factors from the selected factors, rows represent repeated iteration through possible values of the selected secondary factors, and where each row includes a respective risk score based on a weighted average of the respective weights applied to the selected factors represented therein.