Network Request Model for Foreground App Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Parents face challenges in monitoring and limiting their children's use of network-connectable computing devices, as existing operating systems do not provide accessible information on active applications, making it difficult to determine usage patterns and implement control measures.
Innovation Solution
A method involving the monitoring of network requests and DNS requests from user devices, training models to predict foreground applications, and applying these models to restrict device functions or alert supervisory users based on usage trends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If operating systems restrict access to foreground application information, then device security and system integrity are improved, but monitoring capability and parental control effectiveness deteriorate
Solution Approach 1:
The patent introduces intermediary components including a control manager, control agent, and machine learning model that act as mediators between the operating system and parental control systems. These intermediaries capture network request data and application behavior patterns without requiring direct access to restricted foreground application information, thereby maintaining device security while enabling effective monitoring through indirect observation of digital footprint data.
2Measurement precision
If direct monitoring of foreground applications is implemented, then monitoring precision is improved, but device complexity and system resource consumption increase
Solution Approach 1:
The patent replaces direct mechanical monitoring of foreground applications with a machine learning-based inference system. Instead of directly accessing and tracking application states through complex system hooks and APIs, the system uses trained models to predict foreground applications from network request patterns, thereby reducing device complexity while maintaining monitoring precision through intelligent data analysis.
Solution Approach 2:
The patent creates a virtual copy or representation of foreground application information through machine learning predictions. Rather than directly accessing the actual foreground application state, the system generates inferred data that mirrors the information needed for monitoring purposes, reducing the need for complex direct access mechanisms while preserving monitoring effectiveness.
3Adaptability or versatility
If comprehensive network request monitoring is performed across multiple operating systems, then adaptability and cross-platform control are improved, but data processing complexity and model training requirements increase
Solution Approach 1:
The patent implements a universal control manager and control agent architecture that functions across multiple operating systems (iOS, Android, Windows). The machine learning model is trained on aggregated data from diverse platforms and can predict foreground applications regardless of the underlying operating system, enabling single cross-platform parental control accounts to effectively manage devices across different ecosystems without requiring platform-specific implementations.
Data Source
AI summary
A method of controlling use of network-connectable devices is provided. First network requests from a first user device executing a first operating system are monitored, and applications operating in the foreground on the first user device during the first network requests are monitored. A model is trained based on the first network requests and based on the applications respectively operating in the foreground on the first user device during the first network requests. Second network requests from a second user device executing a second operating system are monitored, and the model is applied to the second network requests from the second user device to determine a particular application operating in the foreground on the second user device. A function of the second user device is restricted based on the determining of the particular application operating in the foreground on the second user device.