Blockchain Data Integrity via Credibility Scoring
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Solution Overview
Problem
Existing data protection systems face challenges in maintaining data integrity due to disconnected databases, lack of information sharing, and trust issues among multiple user entities, which can lead to malware, viruses, and ransomware threats affecting backups and restoration processes.
Innovation Solution
A trustless data repository using a distributed ledger, such as blockchain technology, is created to facilitate user consensus on whitelisting and blacklisting files, allowing users to validate and contribute data, with credibility scores and rate limiters controlling entry permissions, ensuring data integrity and trust within a single repository.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple disconnected databases are used to store data integrity information, then each user can manage their own database, but information sharing between users is limited and trust issues arise
Solution Approach 1:
The patent merges multiple disconnected databases into a single shared database that is accessible by multiple users. This allows users to contribute and access threat intelligence collectively, overcoming the information silos present in separate databases while maintaining user autonomy through controlled access rights.
Solution Approach 2:
The shared database serves multiple functions: storing threat intelligence, enabling user contributions, facilitating information sharing, and supporting trust through centralized management. This multi-functional approach replaces multiple specialized databases with one universal system that handles all data integrity needs.
2Ease of manufacture
If multiple databases managed by different entities are used, then each entity can manage their own data, but it becomes unclear which users can be trusted
Solution Approach 1:
The system implements a feedback mechanism where users can report threats and their contributions are reviewed by administrators. This feedback loop allows the system to learn from user inputs, verify their reliability, and adjust access rights accordingly, thereby establishing trust through continuous monitoring and verification.
Solution Approach 2:
An administrator acts as an intermediary between users and the database. Administrators verify user identities, manage access rights, and ensure data quality before entries are added to the shared database. This intermediary role establishes trust by filtering and validating user contributions.
3Loss of information
If a centralized database is used for data integrity information, then information sharing is improved, but administrative overhead increases
Solution Approach 1:
The system segments administrative responsibilities by implementing role-based access control. Different users have different levels of access: some can only read, others can contribute, and administrators have full control. This segmentation reduces the burden on any single administrator while maintaining centralized management benefits.
Solution Approach 2:
The system enables users to perform self-service operations such as reporting threats and accessing information without requiring administrative intervention. This self-service capability reduces administrative overhead while maintaining information sharing effectiveness.
Data Source
AI summary
One example method includes receiving, from an entity, a proposed entry for a ledger, where the ledger is shared and accessible by multiple users and includes a whitelist and a blacklist, determining, or assigning, a credibility score and rate limiter value for the entity, comparing the credibility score and rate limiter value with respective credibility score and rate limiter value thresholds, determining that the credibility score and rate limiter value meet or exceed the respective credibility score and rate limiter value thresholds, and submitting the proposed entry to the ledger.