Cybersecurity Information Valuation Using Target-Aware Richness Scoring
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Solution Overview
Problem
Existing systems require manual evaluation of cyber security information, leading to high man-hours, and fail to consider the relevance of the information to the target field or product, resulting in low value even when the source is reliable and accurate.
Innovation Solution
A computer system that evaluates the freshness, reliability, and richness of cyber security information based on target relevance, automatically determining its value through modules for freshness evaluation, reliability evaluation, richness evaluation, and total evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual evaluation of cyber security information is performed, then the value and accuracy of information assessment is improved, but the man-hours and time required increase significantly
Solution Approach 1:
The evaluation process is divided into three independent modules: freshness evaluation module (evaluates recency and timeliness), reliability evaluation module (evaluates source credibility), and richness evaluation module (evaluates information completeness). Each module independently assesses specific dimensions and outputs scores that are combined to determine overall information value, enabling automated comprehensive evaluation without manual intervention
Solution Approach 2:
The system transforms qualitative assessment criteria into quantitative parameters by measuring freshness as time-based metrics, reliability as source-based scores, and richness as content-based indicators. These parameterized evaluations are computationally processed and combined to produce an automated information value assessment, replacing manual judgment with measurable parameters
2Quantity of substance
If cyber security information is collected from general sources, then the quantity of information is improved, but the relevance to specific target fields or products decreases
Solution Approach 1:
The richness evaluation module performs target-specific assessment by comparing collected information against the specific characteristics, requirements, and context of the target field or product. Each piece of information is evaluated for its relevance and completeness relative to the specific target, ensuring that information quality is tailored to local needs rather than applying uniform standards
Solution Approach 2:
The system dynamically adjusts evaluation criteria and weights based on the specific target being assessed. The richness evaluation adapts to different target types (products, systems, or fields) by modifying what constitutes relevant and complete information, allowing the same collection system to serve multiple targets with varying requirements
Data Source
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AI summary
A computer system comprises a freshness evaluation module configured to evaluate freshness of cyber security information; a reliability evaluation module configured to evaluate a level of reliability of an information source of the cyber security information; a richness evaluation module configured to evaluate richness of a content of the cyber security information; and a value evaluation module configured to evaluate a value of the cyber security information based on evaluation results obtained by the freshness evaluation module, the reliability evaluation module, and the richness evaluation module. The richness evaluation module is configured to: identify a target of application of the cyber security information; and evaluate the richness of the content of the cyber security information in the identified target.