Neural Network Privacy Detection in Electronic Device Image Sharing
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Solution Overview
Problem
Users face the risk of private information exposure when uploading images to various devices, as existing technologies lack effective methods to identify and process sensitive data within images.
Innovation Solution
An electronic device equipped with a neural network model trained to detect private information in images, which displays a user interface to ask for processing options and transmits the image to an external device after user command, allowing for processing of private information areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users upload images to various devices, then image sharing and communication are enabled, but private information in the images may be exposed to the outside
Solution Approach 1:
The system performs preliminary detection of private information in images before upload occurs. The neural network model analyzes the image content in advance, identifies regions containing private information (such as faces, license plates, documents), and prepares processing options for the user before the upload action is completed.
Solution Approach 2:
The system introduces an intermediary processing step between image selection and upload. This intermediary layer includes a user interface that presents detection results and processing options (such as masking, blurring, or cropping) to the user, allowing them to control whether and how private information is processed before the actual upload occurs.
2Object-affected harmful factors
If private information detection and processing functions are added to the electronic device, then user privacy protection is improved, but device complexity increases
Solution Approach 1:
The electronic device leverages its existing multi-functional capabilities (camera, display, processor, communication modules) to perform private information detection and processing. The same hardware components used for general image capture and display are utilized for privacy protection functions, avoiding the need for dedicated specialized hardware and thus limiting the increase in device complexity.
Solution Approach 2:
The system enables the device to automatically detect and manage private information in images without requiring external processing services. The neural network model runs locally on the device, and the user interface is integrated into the device's existing UI framework, allowing the privacy protection functionality to be self-contained within the device itself.
Data Source
AI summary
An electronic device and a method for controlling thereof is provided. The electronic device includes a memory including a neural network model, a display, a communicator including circuitry, and a processor configured to identify, based on a user command to transmit a first image to an external device being input, whether private information of a user is included in the first image by inputting the first image in the neural network model, based on identifying that private information of the user is included in the first image, display a first user interface (UI) asking whether to process at least one private information based on the private information included in the first image, and based on a user command input through the first UI, process the first image and control the communicator to transmit the processed to the external device.