Automated Software Analysis Framework for Unlicensed Content Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Electronic devices lack effective methods to detect and prevent access to unlicensed content, such as copyrighted materials, without user authorization, as existing solutions fail to accurately analyze and identify unauthorized content access by applications.
Innovation Solution
A system and method that collects and analyzes binary data and metadata from applications on electronic devices, using static and dynamic code analysis, and compares network sources of content requests to a whitelist dataset to determine if unlicensed content is being accessed, employing an automated framework that includes a content manager, injection engine, analysis engine, and extraction engine to raise alerts for unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing detection methods are used, then device operation is simple, but detection accuracy of unlicensed content is insufficient
Solution Approach 1:
The detection system is divided into multiple specialized modules: a data collection module that gathers binary data and metadata, a static analysis module that examines code without execution, a dynamic analysis module that monitors runtime behavior, and a determination module that compares findings against licensing information. This segmentation allows each module to focus on specific detection tasks, improving overall accuracy while managing complexity through modular design.
Solution Approach 2:
The system introduces an intermediary determination module that acts as a mediator between the analysis modules and the final detection result. This module collects data from multiple sources, compares network sources of content requests against whitelist datasets, and synthesizes information from both static and dynamic analyses to make accurate determinations about unlicensed content access.
2Reliability
If comprehensive data collection is performed, then detection reliability is improved, but data processing time increases
Solution Approach 1:
The system performs preliminary actions by collecting and organizing binary data and metadata before actual content access occurs. The static analysis module examines code structure and licensing information in advance, creating a baseline for comparison. This preliminary preparation enables faster and more reliable detection during runtime without requiring comprehensive analysis of all possible content access scenarios.
Solution Approach 2:
The dynamic analysis module continuously monitors application behavior during runtime, tracking content requests and comparing them against licensing information in real-time. This continuous monitoring ensures that detection reliability is maintained throughout the application's operation, capturing unauthorized access attempts as they occur rather than requiring periodic checks that would increase processing time.
Data Source
AI summary
Disclosures herein describe methods and systems for detecting unlicensed content that can be accessed by electronic devices using an automated framework for analyzing applications present on the electronic device that allow a user of the electronic device to access unlicensed content.