Vulnerability Prioritization Using Multi-Objective Ranking
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Solution Overview
Problem
Existing systems struggle to efficiently prioritize software patches and vulnerability mitigation actions in computer infrastructure due to multiple simultaneous threats, leading to inefficiencies in addressing data leaks and security issues.
Innovation Solution
A multi-objective optimization method that ranks vulnerabilities based on multiple assessment metrics, using a fitness function to generate a prioritized list of vulnerabilities and infrastructure elements, considering user preferences and dynamic priorities, and applying automated actions to address the highest-risk vulnerabilities first.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple vulnerability threats are addressed simultaneously using traditional methods, then security coverage is improved, but resource efficiency and prioritization effectiveness deteriorate
Solution Approach 1:
The patent segments the vulnerability management process into distinct phases: vulnerability identification, multi-objective assessment (security risk, business impact, exploitability), prioritization ranking, and targeted remediation. This segmentation allows organizations to systematically address multiple vulnerabilities while maintaining resource efficiency by focusing on high-priority items first.
Solution Approach 2:
The patent introduces multiple assessment parameters (security risk score, business impact score, exploitability score) to transform the vulnerability prioritization problem from a single-dimensional to a multi-dimensional evaluation. This parameter transformation enables more accurate prioritization by considering various factors simultaneously, resolving the contradiction between comprehensive security coverage and efficient resource allocation.
2Measurement precision
If comprehensive vulnerability assessment using multiple metrics is performed, then prioritization accuracy is improved, but computational complexity and processing time worsen
Solution Approach 1:
The patent transforms multiple qualitative assessment metrics into quantitative scores with standardized ranges. Each vulnerability is assigned numerical values for security risk, business impact, and exploitability, which can be processed algorithmically. This parameter quantification maintains high prioritization accuracy while enabling efficient computational processing through mathematical operations.
Solution Approach 2:
The patent creates a virtual model of the vulnerability landscape that mirrors the actual infrastructure. This digital representation allows complex multi-metric assessments to be performed on the model rather than directly on the live system, reducing computational overhead and processing time while maintaining assessment accuracy.
3Speed
If automated prioritization systems are implemented, then processing speed and scalability are improved, but system complexity and implementation difficulty worsen
Solution Approach 1:
The patent designs a universal prioritization framework that can handle multiple vulnerability types, assessment metrics, and organizational contexts through a single integrated system. The multi-objective optimization algorithm serves multiple functions: scoring vulnerabilities, ranking them by priority, and generating remediation recommendations. This universality achieves high processing speed and scalability without proportionally increasing system complexity.
Solution Approach 2:
The automated prioritization system performs self-assessment by automatically collecting vulnerability data, evaluating multiple metrics, and generating prioritized remediation plans without requiring extensive manual configuration or intervention. This self-service capability increases processing speed while keeping the system relatively simple to deploy and maintain.
Data Source
AI summary
Techniques are provided for multi-objective computer infrastructure vulnerability prioritization. One method comprises obtaining vulnerabilities associated with computer infrastructure elements; obtaining objectives for ranking the vulnerabilities; determining an initial population of individual solutions for addressing the vulnerabilities, wherein each individual solution comprises a ranked list of vulnerabilities; performing a multi-objective optimization that modifies the initial population of individual solutions to obtain a revised population of individual solutions, wherein each individual solution in the revised population comprises a fitness score and a ranked list of the at least some vulnerabilities; selecting an individual solution in the revised population based on the fitness score; and initiating an automated action to address one or more vulnerabilities in the selected individual solution using the ranked list of at least some vulnerabilities for the selected at least one individual solution.