Network Asset Importance Ranking Using Multi-Source Security Data
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Solution Overview
Problem
Existing methods struggle to accurately evaluate and rank the importance of computer network assets, such as hosts and IP addresses, for entities, as the value or significance of these assets is not easily ascertained without specialized knowledge or tools.
Innovation Solution
A computer-implemented method that evaluates the importance of network assets by receiving datasets related to hostnames, DNS queries, source code, authentication certificates, IP addresses, and other relevant data, and determining input data to calculate host and IP address importance rankings based on various criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to evaluate physical assets, then evaluation can be done by laypersons based on apparent characteristics, but computer network assets cannot be evaluated accurately without specialized knowledge or tools
Solution Approach 1:
The patent introduces an automated evaluation system that acts as an intermediary between network assets and evaluators. The system collects data from multiple sources (DNS queries, source code, authentication certificates, network traffic) and processes it through algorithms to generate objective asset importance rankings, eliminating the need for specialized human knowledge while maintaining high measurement precision.
Solution Approach 2:
The patent replaces manual evaluation methods with automated computational systems. Instead of relying on human experts to assess network asset value, the system uses automated data collection, processing, and ranking algorithms to objectively determine asset importance based on measurable parameters such as DNS query frequencies, certificate validity, and network traffic patterns.
2Measurement precision
If multiple data sources are collected to improve evaluation accuracy, then asset importance ranking becomes more precise, but the complexity of the evaluation system increases
Solution Approach 1:
The patent segments the evaluation system into distinct functional modules: data collection module (gathering DNS queries, source code, certificates, network traffic), data processing module (normalizing and analyzing collected data), and ranking generation module (computing importance scores). Each module handles specific data types and processing tasks independently, reducing overall system complexity while maintaining comprehensive evaluation precision.
Solution Approach 2:
The patent creates a multi-functional evaluation system that can process diverse data types (DNS queries, source code, authentication certificates, network traffic) through a unified framework. The system uses standardized processing pipelines and common output formats that work across different data sources, reducing complexity despite handling multiple evaluation criteria simultaneously.
Data Source
AI summary
Disclosed are computer-implemented methods for ranking importance of assets of an entity, in which the assets can include hosts and/or IP addresses associated with the entity. The exemplary methods can include receiving datasets from one or more sources indicating frequency of system access, system configuration, and/or application configuration. The methods can include determining one or more input data based on the datasets. The methods can include determining, for each host and/or IP address associated with the entity, an importance ranking based on the input data. In some examples, the importance ranking may be based on a weighting of two or more input data.