Automated Device Location Classification via Kernel Tree Analysis

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Current computing devices require manual configuration to classify device connections, limiting the ability to automatically determine the deployment location of devices and enforce specific function enablement or disablement based on connection paths, which is inefficient and prone to errors, especially in environments like point-of-sale terminals.

Innovation Solution

An automated method and system that searches the device tree of a computing device to identify devices of interest, classifies their relative location based on their connection paths, and stores this classification in memory, enabling or disabling device functions accordingly, using the kernel device file system to logically arrange devices in a hierarchical topology.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual configuration is used to classify device connections, then device deployment location classification can be implemented, but the process is inefficient and prone to errors

Engineering Contradiction:
Improveclassification accuracyVSAvoidconfiguration time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The system performs self-service by automatically enumerating devices, identifying their deployment locations through device tree analysis, and classifying them without human intervention. The kernel device file system automatically provides the hierarchical topology information needed for classification, eliminating manual configuration steps while maintaining high accuracy.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system performs preliminary action by pre-establishing the device tree structure and device file system hierarchy before device classification is needed. This pre-organized hierarchical topology allows for rapid automated classification when devices are connected, eliminating the need for manual configuration at deployment time.

Inventive Principle:
Principle #10Preliminary action

2Productivity

If automated device classification is implemented, then configuration efficiency is improved, but system complexity increases

Engineering Contradiction:
Improveconfiguration efficiencyVSAvoidsystem complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The kernel device file system serves multiple functions: it organizes devices hierarchically, provides topology information, and enables automated classification. This universal structure reduces the need for separate specialized systems while improving configuration efficiency through a single multi-functional infrastructure.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The device file system acts as an intermediary layer between the physical device connections and the classification logic. It translates physical connectivity into a standardized hierarchical representation that simplifies automated classification, reducing system complexity by providing a clear mediation interface.

Inventive Principle:
Principle #24Intermediary (Mediator)

3Reliability

If device functions are enabled or disabled based on connection paths, then security is enhanced, but device adaptability is reduced

Engineering Contradiction:
ImprovesecurityVSAvoiddevice function flexibility
Core Design Contradiction:
ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system applies local quality by enabling or disabling device functions based on their specific deployment location in the device tree hierarchy. Devices at different hierarchical levels (e.g., directly connected vs. hub-connected) receive different function configurations, providing security tailored to each location's risk profile while maintaining adaptability for legitimate use cases.

Inventive Principle:
Principle #3Local quality

Data Source

PatentEP3200070B1Coupled device deployment location classification
Publication Date: 2023.01.25 NCR VOYIX CORP
  • EP3200070B1 patent drawingFigure 1
  • EP3200070B1 patent drawingFigure 2
  • EP3200070B1 patent drawingFigure 3

AI summary

Various embodiments herein each include at least one of devices, methods, and software for coupled device deployment location classification in an automated manner. One embodiment, in the form of a method (200 or 300), includes searching a device tree of a computing device (102) to identify any devices of interest (106, 110). This method, for each identified device of interest (106, 110), may then identify a path within the computing device (102) of the device of interest (106, 110) and classify, based on the identified path, a relative location of the device of interest (106, 110). This method may then store the classification of the device of interest (106, 110) in a memory device of the computing device (102).