Network Asset Risk Scoring for Vulnerability Prioritization
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Solution Overview
Problem
Current cybersecurity systems face challenges in detecting vulnerabilities in network assets and prioritizing them effectively due to their complex nature, requiring extensive training and technical expertise for risk assessment.
Innovation Solution
A system and method for evaluating network asset risk through risk scoring, calculating a singular risk score for each asset based on vulnerabilities, exposures, threats, and criticalities, and displaying this on a user interface to facilitate quick security status assessment without the need for extensive user training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a systematic and granular risk assessment approach is conducted to identify and analyze vulnerabilities in network assets, then measurement precision and reliability of risk evaluation are improved, but device complexity and difficulty of operation increase due to requiring technical experts with extensive training
Solution Approach 1:
The risk assessment system segments the complex evaluation process into distinct modular components: vulnerability detection module, threat assessment module, risk calculation module, and prioritization module. Each module handles a specific aspect of risk assessment independently, processing different data types and applying specialized algorithms. This segmentation maintains high measurement precision for each risk dimension while reducing overall system complexity through modular architecture, allowing non-experts to operate the complete system.
Solution Approach 2:
The system introduces an automated risk calculation engine as an intermediary between raw vulnerability data and final risk assessments. This intermediary automatically applies weighted scoring algorithms, combines multiple risk factors, and generates prioritized risk rankings without requiring manual expert intervention. The intermediary translates complex technical data into actionable risk scores that non-expert users can interpret and act upon, maintaining accuracy while eliminating the need for extensively trained specialists.
2Ease of operation
If automated risk scoring is implemented to reduce operational complexity and eliminate the need for technical experts, then ease of operation is improved, but measurement precision may deteriorate due to simplification of assessment processes
Solution Approach 1:
The system employs configurable risk scoring parameters and weighted factors that can be adjusted to match organizational risk tolerance and specific asset criticality. The automated engine uses multiple quantifiable parameters including vulnerability severity, exposure level, threat likelihood, and asset criticality, each with adjustable weights. This parameter-based approach enables non-expert users to operate the system easily while maintaining measurement precision through mathematically rigorous scoring that reflects complex risk relationships without requiring expert judgment.
3Reliability
If comprehensive risk parameters are evaluated for each network asset to improve reliability of risk evaluation, then measurement precision is improved, but loss of time increases due to extensive data collection and analysis requirements
Solution Approach 1:
The system performs preliminary automated actions by continuously collecting and pre-processing vulnerability data, asset inventory information, and threat intelligence before formal risk assessment is triggered. Asset profiles are pre-populated with known vulnerabilities, exposure contexts, and baseline risk metrics. When risk assessment is initiated, the automated engine rapidly retrieves pre-processed data and applies scoring algorithms, eliminating the need for time-consuming manual data collection during the assessment itself. This preliminary automation maintains comprehensive evaluation reliability while dramatically reducing assessment time.
Solution Approach 2:
The risk assessment system operates continuously in the background, constantly monitoring network assets for new vulnerabilities, updating asset inventories, and refreshing threat intelligence data. Rather than performing discrete periodic assessments, the system maintains continuous risk evaluation, automatically detecting and processing security events as they occur. This continuous operation ensures comprehensive reliability by never missing security events while reducing perceived assessment time for users, as the system is always current without requiring manual re-assessment.
Data Source
AI summary
The present disclosure discloses a system and a method for evaluating the risk associated with network assets. More particularly, the present disclosure provides the system and method for evaluating risk associated with network assets based on risk scoring. The disclosed methodology calculates a singular risk score for each network asset. Further, the singular risk score for each network asset is displayed on a web user interface (UI) page to facilitate the user to quickly and efficiently monitor the security status of the network assets without a need for extensive training or technical expertise.