Unwanted Software Detection via File Relationship Analysis
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Solution Overview
Problem
Existing antivirus technologies fail to effectively detect unwanted software installed on computing devices, as they often install with user consent and are masked within larger software installations, making it difficult to distinguish between necessary and unnecessary programs.
Innovation Solution
A system and method that detects unwanted applications by analyzing file relationships, network origin, modification timestamps, and usage frequency, comparing the installation and usage patterns of files and applications to identify and flag unwanted software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standard antivirus detection methods (signature or heuristic) are used, then malicious software can be detected, but unwanted software installed with user consent cannot be detected
Solution Approach 1:
The patent segments the detection process into multiple independent analysis modules: file relationship analysis, network origin analysis, timestamp analysis, and usage frequency analysis. Each module examines a specific aspect of the application, and their combined results enable comprehensive detection of unwanted software that standard methods miss.
Solution Approach 2:
The patent transitions from traditional single-dimension antivirus detection to multi-dimensional analysis by examining file relationships, network origins, modification timestamps, and usage patterns simultaneously. This dimensional expansion allows the system to distinguish unwanted software from legitimate software based on cumulative evidence across multiple parameters.
2Ease of operation
If user consent is obtained during installation, then installation can proceed smoothly, but user awareness of installed programs decreases
Solution Approach 1:
The system performs preliminary analysis of applications during or after installation by examining file relationships, network origins, and usage patterns before the user can make informed decisions about removing unwanted software. This allows detection of potentially unwanted programs that users may not be aware of.
3Productivity
If multiple programs are installed together, then installation efficiency increases, but detection difficulty increases
Solution Approach 1:
The patent merges multiple detection approaches (file relationship analysis, network origin tracking, timestamp comparison, usage frequency monitoring) into a unified detection system. This combination allows the system to handle bundled installations effectively by analyzing the collective behavior and relationships of all installed components.
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor application behavior and file relationships after installation. By tracking usage patterns and modifications over time, the system can identify unwanted software that was installed as part of a bundle, even if initial detection was difficult.
Data Source
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AI summary
Disclosed are system and method for detecting one or more unwanted applications in a computing device. One exemplary method comprises: obtaining information relating to a first application installed on the computing device; detecting a first file associated with the first application; identifying a second file being related to the first file based at least upon selected conditions; identifying a second application installed on the computing device using at least one of the first and second files; determining a frequency of use for each of the first and second applications; and determining whether the first application is an unwanted application based on the frequency of use for each of the first and second applications.