Network Host Risk Scoring for Context-Aware Patch Prioritization
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Solution Overview
Problem
Existing network security systems lack the ability to contextualize vulnerability risks based on host characteristics, leading to inefficient patch management and potential security gaps.
Innovation Solution
A method and system that calculates a vulnerability risk score (VRS) and host risk score (HRS) by considering device category, functionality, use case, and vulnerability metrics, enabling prioritized security patching based on contextualized risk analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional network security systems apply uniform security measures to all hosts, then implementation is simple and consistent, but security effectiveness is reduced due to lack of contextualization
Solution Approach 1:
The patent applies local quality by calculating distinct risk scores for each host based on its specific characteristics including device category, criticality score, and vulnerability profile. Instead of uniform security measures, the system tailors security prioritization to each host's local context, ensuring that critical hosts receive appropriate attention while less critical hosts receive proportionate security management.
Solution Approach 2:
The system changes parameters by introducing multiple dimensional metrics for host assessment including device category (server, workstation, router, etc.), criticality scoring, vulnerability counts, and risk calculations. These parameter changes enable differentiated security management where hosts are prioritized based on their specific parameter profiles rather than treated uniformly.
2Reliability
If security patches are applied to all hosts simultaneously, then comprehensive coverage is achieved, but resource consumption and time requirements increase significantly
Solution Approach 1:
The system performs preliminary action by calculating risk scores and prioritizing hosts before patch deployment. The risk score calculation incorporates device category, criticality assessment, and vulnerability analysis to pre-determine which hosts should be patched first. This preliminary prioritization enables sequential patching starting with highest-risk hosts, reducing overall patch management time while maintaining comprehensive security coverage.
Solution Approach 2:
The patent applies partial action by focusing security patching efforts on hosts that exceed specific risk thresholds rather than treating all hosts equally. The system identifies and prioritizes hosts with high risk scores for immediate patching, while lower-risk hosts can be addressed in subsequent cycles, optimizing resource allocation and reducing total patch management time.
3Measurement precision
If detailed host characteristics are analyzed for each vulnerability, then risk assessment accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The system segments the risk assessment process into distinct analytical components: device category identification, criticality score calculation, vulnerability enumeration, and integrated risk scoring. Each segment processes specific aspects of host characteristics independently, then combines results to produce comprehensive risk assessments. This segmentation improves measurement precision while managing computational complexity through modular processing.
Solution Approach 2:
The patent applies universality by creating a multi-functional risk scoring system that handles multiple host types (servers, workstations, routers, switches, printers, cameras) through a unified analytical framework. The same risk assessment methodology applies across different device categories, enabling consistent measurement precision without requiring separate complex analysis systems for each device type.
Data Source
AI summary
A method includes scanning a network having a first and second host, obtaining, via the scanning, a first and second type information of the first and second host, respectively, the first or second type information including a device category, obtaining, via the scanning, a first and second scaling factor of the first and second host, respectively, calculating, a first criticality score of the first host based on the first type information and the first scaling factor, calculating a second criticality score of the second host based on the second type information and the second scaling factor, calculating a first host risk score (HRS) for the first host based on the first criticality score, calculating a second HRS for the second host based on the second criticality score, and applying a security patch on the first host prior to the second host first HRS is higher than the second HRS.