Network Risk Assessment via Active Scanning and Logistic Modeling
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Solution Overview
Problem
Current network risk management technologies rely on passive analysis, which is inadequate for real-time vulnerability detection and lacks flexibility to provide custom assessments based on specific risk profiles, often resulting in inaccurate and stale data.
Innovation Solution
A method involving active scanning and flexible definitions for network risk management, including sampling networks, assessing security features, ranking them based on risk, transforming factors into categorized elements, and building a logistic model that blends these factors into a likelihood of breach, with real-time configurability and customization options through a graphical user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If passive analysis is used to determine network risk, then system complexity is reduced, but measurement precision and timeliness of vulnerability detection deteriorate
Solution Approach 1:
The patent replaces passive mechanical analysis with active automated scanning systems that use software agents to proactively detect vulnerabilities. This substitution enables real-time, precise vulnerability identification without manually increasing system complexity, as the automation handles the complexity internally.
Solution Approach 2:
The patent introduces risk assessment models and scoring systems as intermediaries between raw scan data and risk decisions. These models process and interpret vulnerability data, providing precise risk measurements while keeping the overall system architecture manageable through modular design.
2Device complexity
If fixed analysis approaches are used, then device complexity is reduced, but adaptability to specific risk profiles deteriorates
Solution Approach 1:
The patent implements dynamic risk assessment models that can be configured and adjusted based on specific organizational risk profiles. The system allows users to modify assessment parameters, weights, and criteria through graphical interfaces, enabling adaptability without requiring complex custom development for each scenario.
Solution Approach 2:
The patent enables customization by allowing users to change parameters such as risk weights, assessment criteria, and scanning configurations. These parameter adjustments let organizations tailor the risk assessment to their specific needs while maintaining the underlying system structure.
3Device complexity
If historical data is used for risk assessment, then data collection complexity is reduced, but measurement precision and timeliness deteriorate
Solution Approach 1:
The patent performs vulnerability scans and risk assessments proactively before breaches occur, rather than relying on historical breach data. This preliminary action ensures current, accurate risk measurements by detecting vulnerabilities in real-time before they can be exploited.
Solution Approach 2:
The patent implements continuous monitoring and recurring scanning capabilities that maintain up-to-date risk assessments. This continuous action ensures risk data remains current and accurate without requiring complex manual updates or relying on stale historical information.
Data Source
AI summary
A method of building a risk management model, the method including: sampling a plurality of organization networks; assessing identified security features; ranking the identified security features based on security risk; transforming ranked features into categorized factors; building logistic model to blend the categorized factors into a likelihood of breach; and transforming the logistics model from a multiplicative model to an additive model by scaling the logistics model.