Distributed Information Generator with Check Data for Tamper Detection
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Solution Overview
Problem
Conventional secret sharing schemes face challenges in detecting tampered data during the restoration of confidential information, particularly when distributed information is obtained based on any probability distribution, and they require a large amount of distributed information compared to the confidential information.
Innovation Solution
A system that generates check data corresponding to the confidential information, distributes and stores it alongside the confidential information, and upon restoration, verifies if the check data corresponds to the restored confidential information to detect tampered data, using a smaller data set for check data to reduce the overall amount of distributed information required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional secret sharing schemes are used to detect tampered data, then the detection capability is improved, but the amount of distributed information becomes excessively large
Solution Approach 1:
The distributed information is segmented into two distinct components: confidential information and check data. Each participant receives a segmented portion containing both types of data. This segmentation allows the system to detect tampering through the check data without requiring excessive redundancy in the confidential information itself, thus resolving the contradiction between detection capability and information quantity.
Solution Approach 2:
Check data acts as an intermediary element between the confidential information and the detection process. Rather than directly embedding detection mechanisms within the confidential information (which would increase its size), the check data serves as a separate mediator that enables tampering detection. This intermediary approach allows reliable detection while maintaining the confidentiality and minimizing the size of the primary information.
2Measurement precision
If check data is generated and distributed alongside confidential information, then the detection rate of tampered data is improved, but the overall data size increases
Solution Approach 1:
The system changes the parameter of data composition by introducing check data with specific properties (smaller size relative to confidential information, different functional characteristics). The check data is designed with parameters that enable high detection rates through mathematical relationships (such as linear dependencies in secret sharing schemes) without proportionally increasing the overall data size. This parameter optimization resolves the contradiction between detection precision and data quantity.
Data Source
AI summary
Check data corresponding to distributed confidential information is generated, and the confidential information and check data are distribution-coded. When the confidential information is restored, the confidential information and check data are restored and it is determined whether or not the restored check data correspond to the restored confidential information. If the data correspond to the information, the information is determined to be correct and is output. If not, the information is judged to be false (i.e., tampered distributed information), and a symbol indicating that falsity has been detected is output.