Multi-feature Risk Analysis Model for Asset Prioritization
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Solution Overview
Problem
Organizations face challenges in effectively prioritizing and managing assets due to the lack of correlation between diverse datasets related to threat, vulnerability, and business criticality data, making it difficult to implement a clear asset risk management process for risk mitigation.
Innovation Solution
A method and system for multi-feature risk analysis that generates a risk score for assets by correlating threat, vulnerability, and business criticality data, using a risk model that calculates threat and vulnerability risk levels, and assigns weights to determine an overall risk score, allowing for customization and fine-tuning based on specific organizational needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple diverse datasets (threat, vulnerability, business criticality) are collected for comprehensive risk analysis, then the completeness and accuracy of risk assessment is improved, but the complexity of data correlation and processing increases
Solution Approach 1:
The patent merges multiple diverse datasets (threat data, vulnerability data, business criticality data) into a unified risk score through a standardized calculation model. This combines heterogeneous data sources with different formats and meanings into a single integrated assessment, resolving the contradiction by achieving comprehensive accuracy while managing complexity through unification.
Solution Approach 2:
The patent transforms diverse data parameters from different datasets into a standardized risk score parameter through weighted calculations. By changing the parameter representation from multiple diverse metrics to a unified score, the system maintains assessment accuracy while simplifying the complexity of data correlation.
2Ease of operation
If a standardized risk score model is implemented to prioritize assets, then the ease of operation and decision-making is improved, but the adaptability to specific organizational needs may be reduced
Solution Approach 1:
The patent implements a dynamic risk score model where weights and parameters can be adjusted based on organizational needs while maintaining the standardized calculation framework. This allows the model to adapt to different scenarios and requirements without losing the operational simplicity of a unified scoring system, resolving the contradiction between ease of use and adaptability.
3Reliability
If detailed multi-factor risk analysis is performed for each asset, then the reliability of risk identification is improved, but the loss of time and computational resources increases
Solution Approach 1:
The patent performs preliminary data collection and standardization for threat, vulnerability, and business criticality factors before the actual risk calculation. By preparing and organizing data in advance according to the standardized model requirements, the system reduces the time needed for detailed analysis while maintaining reliable multi-factor assessment through pre-processed inputs.
Data Source
AI summary
An embodiment defines a risk model that generates a risk score for an asset based on a plurality of factors, including a first factor that is a first factor type and a second factor that is a second factor type. The model includes a plurality of associations, including a first association that associates a first factor weight with a specified significance of the first factor, and a second association that associates a second factor weight with a time-based metric of the second factor. The embodiment includes modifying one of the plurality of associations resulting in a modified risk model, and generating, using the modified risk model, a risk score for the asset, the generating including determining the risk score for the asset based at least in part on a first factor weight value of the first factor weight and a second factor weight value of the second factor weight.