Management Device for Secure Image Data Distribution
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Solution Overview
Problem
Existing systems fail to securely manage and reproduce high-resolution image data while ensuring copyright and privacy security in network environments, particularly for content and surveillance videos, as they lack effective methods for distributing and reconstructing image data with varying resolutions and security levels.
Innovation Solution
An image processing system employing a management device that uses reversible secret sharing schemes to divide video data into multiple resolutions and distribute it across multiple storage units, allowing reconstruction with a varying number of pieces based on resolution, ensuring security through the use of a threshold-based secret sharing method.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video data is distributed into multiple pieces for security, then copyright and privacy security are improved, but the ability to reproduce high-resolution image data requires gathering more pieces which increases system complexity
Solution Approach 1:
The patent applies segmentation by dividing video data into multiple distributed pieces using secret sharing schemes. Each piece can be accessed independently, and a threshold number of pieces are required to reconstruct the original high-resolution data. This segmentation enables security through distribution while maintaining the ability to reproduce high-quality images when sufficient pieces are gathered.
Solution Approach 2:
The patent implements dynamics by allowing the number of required pieces to vary based on resolution requirements. Different resolution levels can be reconstructed from different numbers of pieces, enabling the system to adapt dynamically to user needs and authority levels. This dynamic approach balances security with accessibility.
2Manufacturing precision
If more distributed data pieces are gathered to reproduce high-resolution image data, then image quality is improved, but the threshold for accessing different resolution levels increases
Solution Approach 1:
The patent applies local quality by assigning different access thresholds to different resolution levels. Higher resolution data requires more pieces (higher threshold) while lower resolution data requires fewer pieces (lower threshold). This allows the system to provide high image quality when needed while maintaining ease of access for lower quality requirements.
Solution Approach 2:
The patent uses parameter changes by varying the threshold parameter based on the desired resolution level. The system can change the number of required pieces as a parameter to control access to different quality levels, enabling flexible management of image quality versus access ease.
3Reliability
If a threshold-based secret sharing scheme is used to ensure security, then copyright and privacy protection are improved, but the complexity of data reconstruction increases
Solution Approach 1:
The patent applies preliminary action by pre-establishing the threshold parameters and distributing pieces according to predefined authority levels before actual access is needed. This preliminary setup simplifies the reconstruction process during use, as users only need to gather the required number of pieces according to their authority level without complex calculations.
Solution Approach 2:
The patent uses copying by creating multiple copies of the data distributed across different pieces. The threshold-based secret sharing scheme allows reconstruction from a subset of copies, providing security through distribution while keeping reconstruction relatively simple through standard threshold reconstruction algorithms.
Data Source
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AI summary
A resolution converter converts input image data to N types (N is a plural number) of image data having resolutions different with each other. A secret sharing unit performs secret sharing schemes so that the plurality of pieces of image data are respectively divided into n pieces (n is an integer equal to or more than N+1 and the same value in all of image data) of distributed data and the distributed data is reconstructed to original image data using k pieces (k is an integer equal to or more than 2 and equal to or less than n and different value for each piece of image data) among n pieces. A data combination unit generates n pieces of combination data by combining distributed data selected one by one so as not to overlap with each of resolutions and stores each piece of the combination data in different storages. As more pieces of distributed data are gathered, image data with higher resolutions can be reproduced and security for copyright, privacy, or the like can be secured in each piece of distributed data.