Version-Specific Vulnerability Scoring for Software Risk Assessment
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Solution Overview
Problem
Managing computer software and hardware issues related to confidentiality, integrity, and availability is challenging due to variations across different versions and environments, making it difficult to assess and mitigate risks effectively.
Innovation Solution
A system for obtaining and processing issue information from vendors and centralized data sources to generate version-specific scores for software and hardware, allowing users to prioritize and compare different versions based on confidentiality, integrity, and availability scores, which can be configured according to user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If issue information is collected from multiple sources and versions are compared, then the accuracy of risk assessment is improved, but the complexity of the system increases
Solution Approach 1:
The patent segments the risk assessment process into distinct components: collecting issue information from multiple sources (vendors, centralized databases), processing information for each software version separately, generating scores for individual versions, and then comparing versions. This segmentation allows the system to handle complex multi-source data by breaking it into manageable version-specific assessments, improving accuracy while controlling complexity through modular processing.
Solution Approach 2:
The patent performs preliminary actions by pre-collecting and storing issue information from multiple sources before the actual assessment is needed. Issue information is gathered and processed in advance, creating a database of known issues that can be quickly retrieved and applied to version comparisons. This preliminary data preparation reduces the complexity of real-time assessment while maintaining high accuracy.
2Loss of information
If version-specific scores are generated for multiple software versions, then the ability to make informed decisions is improved, but the time required for assessment increases
Solution Approach 1:
The patent generates and stores issue information for multiple software versions in advance, creating a pre-processed database of version-specific issues and scores. When a user needs to compare versions, the system retrieves pre-generated scores rather than performing complete assessments in real-time. This preliminary generation of version-specific data maintains high decision-making quality while significantly reducing the time required for actual version comparison and selection.
3Reliability
If comprehensive issue information is processed, then the reliability of the scoring system is improved, but the difficulty of processing increases
Solution Approach 1:
The patent divides comprehensive issue information processing into version-specific segments. Each software version is assessed independently, with issues collected, processed, and scored separately for each version. This segmentation allows the system to maintain high reliability by considering all available issue information while reducing processing difficulty through modular, version-by-version analysis rather than attempting to process all version data simultaneously.
Data Source
AI summary
In examples, vulnerability information is obtained from vendors/manufacturers and/or centralized data sources and processed to extract information about associated issues. Additionally, one or more scores (e.g., a confidentiality score, an availability score, and/or an integrity score) may be generated for hardware and/or software based on a set of associated issues. A score may be version-specific, such that different versions of software may each have different associated scores. A set of generated scores may each be used as a score component to generate an aggregated score for the hardware and/or software (e.g., by weighting security and/or operational issues differently). In some instances, an organization may prioritize confidentiality over availability or vice versa, such that an aggregated score reflects a user-configured weighting. Aggregated scores for multiple hardware and/or software versions may be ranked or presented to a user, thereby enabling a user to determine whether one version is preferable to another version.