Client-Side Web Control with Real-Time Content Analysis
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Solution Overview
Problem
Traditional parental control tools and web filtering software rely on static blacklists and whitelists, which are ineffective in classifying dynamic internet content, such as real-time messages and social network interactions, and can be easily bypassed using VPNs, leading to inadequate protection for internet users, particularly children and students.
Innovation Solution
A client-based web control system that performs real-time analysis and classification of web content on user devices, using machine learning models to identify and filter inappropriate content before it is displayed, and optionally verifies classifications with a cloud server to enhance accuracy and scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If static blacklist/whitelist methods are used for web content filtering, then the control mechanism is simple to implement, but the classification accuracy of dynamic web content is poor
Solution Approach 1:
The patent transforms the static filtering mechanism into a dynamic one by implementing real-time content analysis that adapts to changing web content characteristics. The system continuously monitors and classifies content as users interact with websites, enabling accurate classification of dynamic content such as social media posts, chat messages, and video streams that static lists cannot handle.
Solution Approach 2:
The patent replaces the mechanical approach of static keyword matching with intelligent content analysis techniques. Instead of relying on predetermined lists, the system uses contextual understanding and pattern recognition to classify content dynamically, substituting rigid mechanical filtering with adaptive intelligent analysis.
2Adaptability or versatility
If proxy server is used for web filtering, then centralized control is achieved, but the system can be easily bypassed and cannot be scaled up
Solution Approach 1:
The patent introduces a client-side content analysis component that acts as an intermediary between the user's browser and the web content. This local agent performs content classification directly on the user's device, eliminating the single point of failure that proxy servers create and making bypass attempts ineffective since the filtering occurs client-side rather than at the network level.
Solution Approach 2:
The system enables each user device to perform its own content analysis and filtering independently. Each client device runs the content analysis engine locally, allowing it to autonomously classify and filter content without relying on external proxy servers, thereby achieving both scalability and bypass resistance.
3Loss of time
If pre-crawl method is used to capture web content, then initial content classification is possible, but dynamic content such as login-required pages and real-time messages cannot be accessed
Solution Approach 1:
The patent performs preliminary content analysis at the point of delivery rather than in advance. By analyzing content as it is being received by the user's device, the system can classify dynamic content that becomes available during user interaction, including login-required pages, real-time chat messages, and user-generated content that cannot be captured by pre-crawling.
Solution Approach 2:
The system maintains continuous content analysis throughout the user's browsing session rather than performing a one-time pre-crawl. This continuous monitoring ensures that all dynamic content, including real-time updates, messages, and interactively loaded content, is captured and classified as it becomes available, providing comprehensive coverage of evolving web content.
Data Source
AI summary
The present disclosure describes a client-based web control system for analyzing and filtering web content received at a user device and presenting the filtered content on the user device in real-time, one or more operations and functions being efficiently achieved via this system comprise: receiving, at a user device, web content; identifying, at the user device, at least one model for classifying the web content; performing, at the user device, real-time analysis on the web content using the at least one model to classify the web content and determine a classification result; and taking an action on the web content at the user device based on the classification result. The present disclosure also describes the web control system including a cloud server, which, in conjunction with the user device, analyzes and classifies the web content.