Cross-Asset Group Characterization for Network Vulnerability Detection

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Solution Overview

Problem

Existing systems struggle to effectively characterize and manage asset groups spanning multiple asset classes in a computer network, leading to inefficiencies in identifying relationships and vulnerabilities across diverse assets.

Innovation Solution

A method that aggregates attributes from various sources into asset containers, identifies associations between assets, and defines attribute categories to group assets based on predefined combinations, enabling real-time risk assessment and automated actions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If existing systems are used to characterize asset groups, then asset management is simplified, but the ability to effectively identify relationships and vulnerabilities across diverse assets deteriorates

Engineering Contradiction:

Improveasset managementVSAvoidvulnerability detection accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent segments assets into different asset classes (infrastructure assets, software assets, data assets) with specialized characterization methods for each class. This segmentation allows precise vulnerability identification within each asset type while maintaining overall system manageability through class-based organization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent creates a universal asset group characterization framework that works across multiple asset classes. The system universally applies association rule mining and attribute category definitions to diverse asset types, enabling consistent vulnerability detection methodology while adapting to specific asset class characteristics.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Measurement precision

If comprehensive asset characterization is implemented across multiple asset classes, then vulnerability detection capability is improved, but system complexity increases

Engineering Contradiction:

Improvevulnerability detection capabilityVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent adds a new dimension of asset group characterization by introducing attribute categories and association rules as additional layers of analysis. This dimensional expansion enables comprehensive vulnerability detection across asset classes without fundamentally complicating the base asset management structure.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The patent introduces asset groups as intermediary entities that bridge individual assets and vulnerability analysis. By grouping assets with similar characteristics and relationships, the system simplifies the complexity of analyzing individual assets while maintaining comprehensive vulnerability detection capability.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Reliability

If asset associations across different asset classes are identified, then risk assessment accuracy is improved, but data processing requirements increase

Engineering Contradiction:

Improverisk assessment accuracyVSAvoiddata processing volume

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The patent extracts only the most relevant attributes and associations from the full asset data for risk assessment. By identifying and focusing on key association rules between asset classes, the system achieves accurate risk assessment while processing only the essential data subset rather than all available information.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent transforms raw asset data into standardized attribute categories and association rules, changing the parameters from detailed individual asset attributes to grouped characteristic parameters. This parameter transformation reduces data volume while preserving the essential information needed for accurate cross-asset risk assessment.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12524812B2Method for characterizing asset groups spanning multiple asset classes in a computer network

Publication Date: 2026.01.13 ARCTIC WOLF NETWORKS INC

AI summary

A method includes: accessing a first set of attributes exhibited by a first asset during a time interval; identifying a first association between the first asset and a second asset based on the first set of attributes; accessing a second set of attributes exhibited by the second asset during the time interval; based on the first association between the first asset and the second asset, associating the first asset with a first subset of attributes in the second set of attributes; identifying an asset group, including the first asset, exhibiting a target combination of attributes during the time interval based on the target combination of attributes represented in the first set of attributes and the first subset of attributes, in the second set of attributes, associated with the first asset; and executing an action on assets in the asset group.