Image-Derived Encryption Keys for Crack-Resistant File Protection
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Solution Overview
Problem
Current data protection methods, such as fingerprint, face ID, pattern, voice, and password unlocking, are vulnerable to cracking, posing a risk of confidential file leakage and insufficient security.
Innovation Solution
A data protection method that generates an encryption key by analyzing characteristic values from real-time images captured using an electronic device, employing techniques like convolutional neural networks and SURF algorithms to create a dynamic encryption key for secure file encryption and decryption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional unlocking methods (fingerprint, face ID, pattern, voice, password) are used, then ease of operation is improved, but security reliability deteriorates due to vulnerability to cracking
Solution Approach 1:
The patent changes the fundamental parameter of authentication from static biometric data or passwords to dynamic image characteristic values. By extracting multiple characteristic values (edges, corners, contours, textures) from real-time images and combining them into encryption keys, the system transforms the authentication parameter space to achieve both high security and user convenience.
Solution Approach 2:
The patent combines multiple different types of image characteristic values (edges, corners, contours, textures, colors) into a composite encryption key. This composite approach integrates multiple security layers within a single authentication mechanism, making the system resistant to various cracking methods while maintaining ease of operation.
2Reliability
If encryption keys are generated from image characteristic values, then data security is improved, but device complexity increases due to multiple processing steps
Solution Approach 1:
The patent segments the image analysis process into distinct modules: edge detection, corner detection, contour extraction, texture analysis, and color identification. Each module independently extracts specific characteristic values that are then combined to form the encryption key. This segmentation reduces processing complexity by making each step manageable and reusable.
Solution Approach 2:
The patent performs preliminary extraction and storage of image characteristic values during the encryption phase. These characteristic values are saved and can be quickly retrieved and combined during decryption, eliminating the need to re-process the entire image analysis pipeline and reducing real-time processing complexity.
3Reliability
If multiple image characteristic values are extracted and combined, then encryption key security is improved, but processing time increases
Solution Approach 1:
The patent extracts and stores multiple image characteristic values in advance during the key generation phase. These pre-extracted characteristic values are saved in a structured format, allowing for rapid retrieval and combination during decryption operations, thereby reducing the time penalty associated with processing multiple characteristic values.
Solution Approach 2:
The patent merges multiple different types of image characteristic values (edges, corners, contours, textures, colors) into a single unified encryption key through systematic combination rules. This merging process consolidates multiple security layers into one key structure, maintaining high security while optimizing processing efficiency by avoiding redundant operations.
Data Source
AI summary
A data protection method is provided. The data protection method includes the following. A first image is obtained; at least one first object image in the first image is identified; the at least one first object image is analyzed to capture multiple first characteristic values of multiple characteristic points of the at least one first object image; and an encryption key is generated according to the first characteristic values.