Vulnerability Risk Ranking Using Multi-Factor Maturity Scoring
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Solution Overview
Problem
Existing vulnerability management systems face challenges in prioritizing security control checks with tied Capability Maturity Model Integration (CMMI) scores, making it difficult to determine the sequential order for maturity improvements.
Innovation Solution
A dynamic prioritization system, referred to as the TIE³B model, integrates CMMI scores with additional dimensions such as time, impact, effort, expense, exploitability, and building block weight to generate a prioritization score, using machine learning models to refine the ordering of security controls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CMMI scoring is used to evaluate vulnerability management components, then a standardized maturity assessment is achieved, but the ability to differentiate and prioritize components with tied scores is lost
Solution Approach 1:
The patent introduces additional evaluation dimensions beyond the single CMMI score by incorporating multiple VASCR elements (time, impact, effort, expense, exploitability, building block weight). Each element adds a new dimension to the assessment space, transforming the problem from 1D (single score) to multi-D (multiple criteria), enabling differentiation of components that were previously tied.
Solution Approach 2:
The system changes the parameters of evaluation by moving from a single maturity level parameter to multiple weighted parameters (VASCR elements). Each parameter represents a different aspect of vulnerability management effectiveness, and their combined weighted assessment transforms tied CMMI scores into differentiated prioritization scores.
2Measurement precision
If multiple evaluation criteria are integrated to break ties, then prioritization accuracy is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal prioritization framework that can assess multiple vulnerability management components using the same set of VASCR elements and weighting mechanisms. This multi-functional system handles diverse component types (scanners, patch management, configuration management) through a unified evaluation approach, managing complexity through standardization.
Solution Approach 2:
The system introduces an intermediary prioritization score that mediates between the multiple VASCR elements and the final component ranking. This intermediary calculation layer aggregates the weighted elements into a single prioritization metric, simplifying the decision-making process while maintaining the benefits of multi-criteria evaluation.
3Measurement precision
If manual assessment of multiple VASCR elements is performed, then assessment thoroughness is improved, but time and resource consumption increase
Solution Approach 1:
The system enables automated self-assessment where the vulnerability management components themselves provide data for the VASCR elements through integrated data collection mechanisms. The assessment system automatically gathers information about time, impact, effort, expense, exploitability, and building block weight without requiring manual input for each element, reducing time consumption while maintaining thoroughness.
Solution Approach 2:
The patent implements feedback loops where assessment results are used to automatically adjust and refine the evaluation process. The system learns from previous assessments and automatically optimizes data collection, reducing redundant manual efforts in subsequent evaluations while maintaining or improving assessment quality.
Data Source
AI summary
Mechanisms are provided for assessing control checks and components of a vulnerability management system (VMS) for a computing infrastructure. A security vulnerability risk gap assessment of the VMS is executed to generate result data for a plurality of control checks. For each control check, the mechanisms: classify the control check into a maturity level having a corresponding maturity level value; classify each of a plurality of vulnerability assessment security control rating (VASCR) elements into a predetermined classification having corresponding classification values for the control check; and combine the maturity level value and the VASCR element classification values to generate a prioritization score. A graphical user interface output is generated comprising a representation of a prioritized ranked listing of control checks based on the prioritization scores associated with each of the control checks in the plurality of control checks.