Live GUI Text Masking Using Server-Side OCR Mediation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies fail to effectively and efficiently provide robust image masking in live image sharing applications across different software programs and platforms, particularly in contexts involving sensitive text, leading to computational inefficiencies and security risks.
Innovation Solution
A system utilizing a secure server to act as an intermediary between client devices, employing OCR and classification models to identify and mask sensitive text in real-time, while offloading computationally expensive tasks from client devices, ensuring secure and platform-agnostic image masking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image masking is performed on client devices using existing technology, then sensitive text can be masked, but computational burden and processing time increase significantly
Solution Approach 1:
The patent introduces a server as an intermediary between the user device and the agent device. The server performs the computationally intensive OCR and classification tasks for identifying and masking sensitive text, while the user device only needs to capture and transmit images. This distributes the computational burden from the client device to the server, resolving the contradiction between reliable masking and reduced computational burden.
2Reliability
If platform-specific masking solutions are implemented, then masking functionality can be provided, but software compatibility across different platforms is limited
Solution Approach 1:
The patent implements a universal masking solution where the server performs OCR and classification tasks that are platform-agnostic. The system can process images from any client device regardless of the operating system or software platform, as all processing is centralized on the server. This resolves the contradiction by providing universal masking functionality that adapts to all platforms without requiring platform-specific implementations.
3Reliability
If real-time masking is implemented in live image sharing, then security is improved, but processing speed and latency increase
Solution Approach 1:
The system performs preliminary actions by pre-processing images on the server side before they are shared in real-time communication. The OCR model extracts text and the classification model identifies sensitive content in advance, allowing the masking to be applied immediately when images are transmitted. This preliminary processing on the server enables real-time masking without significant latency, resolving the contradiction between security and processing speed.
Data Source
AI summary
Various embodiments are directed to apparatuses, methods, computer-readable media, computer program products, and systems related to, responsive to an actuation of an interactive element of a graphical user interface associated with a software application operating on a client device, receiving (i) a captured image representative of at least a portion of the graphical user interface and (ii) context data associated with the software application and/or the client device; executing a multimodal diagnostic inference engine to: extract, via an optical character recognition (OCR) model using the captured image, text from the captured image; generate, using the extracted text and the context data, a context-aware fault point indicator characterizing a fault associated with the software application and/or client device; and generate, using the context-aware fault point indicator and a retrieval-augmented diagnostic repository, a context-aware fault resolution; and transmitting the context-aware fault resolution to the software application to cause resolution of the fault.