Client-Side Screen Recording Validation for Privacy
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Solution Overview
Problem
Current methods for monitoring user behavior online, such as using VPNs, face limitations including privacy concerns, operating system compatibility issues, inability to track non-network actions, and inefficient data collection processes, necessitating a more secure and efficient approach.
Innovation Solution
A system that involves client-side and server-side validation of screen recordings to extract structured data from user interactions, where screen recordings are validated at the client device for characteristic markers before being uploaded, and further processed at a server to generate structured data, ensuring privacy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If VPN-based traffic monitoring is used to collect user behavior data, then data collection capability is improved, but user privacy protection deteriorates due to collection of sensitive data
Solution Approach 1:
The patent extracts and processes only the necessary data elements needed for user behavior analysis while excluding sensitive personal information. Screen recordings are processed to extract behavioral patterns without capturing or transmitting identifiable sensitive data, thus separating useful information from harmful sensitive content.
Solution Approach 2:
The patent introduces an intermediary processing layer that anonymizes and aggregates user behavior data before analysis. This intermediary system transforms raw screen recordings into processed behavioral metrics, acting as a buffer that protects user privacy while maintaining data collection effectiveness.
2Productivity
If VPN-based traffic monitoring is used, then internet traffic can be tracked, but compatibility with different operating systems deteriorates
Solution Approach 1:
The patent implements a universal screen recording mechanism that functions across multiple operating systems including Windows, macOS, and mobile platforms. The system uses standardized screen capture APIs and processing methods that are adaptable to different OS environments, eliminating the need for VPN-based solutions and achieving broad compatibility while maintaining monitoring capability.
3Productivity
If VPN-based traffic monitoring is used, then network traffic can be captured, but ability to track device-level actions deteriorates
Solution Approach 1:
Instead of capturing network traffic and trying to infer user actions (the VPN approach), the patent inverts the methodology by directly capturing screen recordings and extracting behavioral information from visual content. This inversion enables comprehensive tracking of device-level actions including local file operations, offline applications, and user interactions that never generate network traffic.
4Quantity of substance
If traffic monitoring is performed for extended periods before parsing, then comprehensive data can be collected, but data processing efficiency deteriorates
Solution Approach 1:
The patent performs preliminary processing of screen recordings during or immediately after capture, extracting key behavioral features and metadata in real-time. This preliminary action reduces the complexity and volume of raw data that requires later analysis, enabling efficient processing while maintaining comprehensive data collection. The system prepares data structures and identifies important events during capture rather than waiting for batch processing.
Data Source
AI summary
Device-side validation of screen recordings is disclosed, including: accessing a screen recording of a user's activities on a client device with respect to a task; performing, at the client device, video validation on the screen recording, including by identifying a characteristic marker associated with the task within the screen recording; and in response to the characteristic marker being identified, sending at least a portion of the screen recording to a compressed version of the screen recording to a server for further processing.