Software Detection via User Identifier Probability Thresholds
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Solution Overview
Problem
In complex IT environments, there is a mismatch between software registered in catalogs and software actually installed on computing systems, making it difficult to manage computing systems and user licenses in compliance with rules and contractual requirements.
Innovation Solution
A method that compares default user identifiers from a software catalog with installed user identifiers on a computer system, assigning a probability value based on matching identifiers and applying a threshold comparison to determine if software is installed, with additional methods to confirm the presence of software for increased accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional software catalog registration methods are used, then software inventory management is simplified, but accuracy of detecting actually-installed software deteriorates
Solution Approach 1:
The patent replaces manual software catalog registration with an automated detection system that uses machine learning models to analyze user identifiers and determine actual software installation status, substituting human-operated mechanical processes with automated computational analysis
Solution Approach 2:
The patent introduces user identifiers as an intermediary element to bridge the gap between software catalog records and actual installation status, using these identifiers as mediators to train machine learning models that can accurately detect installed software without direct system access
2Measurement precision
If comprehensive detection methods are implemented, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the detection process into distinct components: collecting user identifiers, training separate machine learning models for different software types, and implementing modular detection logic, allowing the complex system to be managed through independent, manageable segments
Solution Approach 2:
The patent changes the detection parameter from direct software file analysis to user identifier pattern recognition, transforming the detection approach to use probabilistic scoring based on identifier matching rather than exhaustive system scanning, thereby reducing complexity while maintaining accuracy
Data Source
AI summary
A method for detecting software installed on a computer may be provided. The method may comprise obtaining a default user identifier, collecting an installed user identifier, performing an identifier comparison by comparing the installed user identifier with the default user identifier and determining whether an installed user identifier matches a default user identifier, assigning a probability value based on the identifier comparison, performing a threshold comparison of the probability value to the a predetermined threshold value, determining whether the probability value exceeds the threshold value, and in response to determining that the probability value exceeds the threshold value, concluding that the software has been installed on the computer system.