Blockchain Consensus Anomaly Detection via Node Segmentation
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Solution Overview
Problem
Current technologies fail to provide efficient and reliable solutions for determining the validity of documents and detecting malicious network nodes in blockchain networks, leading to vulnerabilities in information security and unauthorized access to confidential information.
Innovation Solution
A system and method that utilize a network interface and processor to verify document validity by comparing extracted user information with corresponding information from network nodes, and establish consensus among nodes to detect anomalies and ensure the integrity of document validity, even in the presence of failures or anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If document validation is performed by comparing information with network nodes, then information security is improved, but system complexity increases due to distributed consensus requirements
Solution Approach 1:
The system segments the validation process into multiple independent network nodes, each maintaining copies of user information. This distribution of validation functions across multiple nodes enhances security through decentralization while managing complexity through modular architecture
Solution Approach 2:
The patent introduces a consensus mechanism as an intermediary layer that coordinates between multiple network nodes. This mediator manages the complexity of distributed validation by establishing standardized protocols for information comparison and consensus achievement
2Reliability
If consensus is established among multiple network nodes, then fault tolerance is improved, but validation time increases due to coordination overhead
Solution Approach 1:
The system requires consensus from a threshold number of nodes rather than all nodes, enabling partial action. This approach achieves sufficient fault tolerance by validating against a subset of nodes, reducing coordination time while maintaining reliability even when some nodes are unavailable
Solution Approach 2:
Network nodes pre-cache user information and validation rules before validation requests arrive. This preliminary preparation reduces real-time coordination overhead during actual validation, allowing faster consensus achievement while maintaining fault tolerance
3Reliability
If user information is stored across distributed nodes, then data integrity is improved, but information access efficiency decreases due to multiple queries
Solution Approach 1:
The system creates distributed copies of user information across multiple network nodes. Each node maintains identical copies, ensuring data integrity through replication. The copying mechanism allows any node to serve validation requests, maintaining access efficiency despite distribution
Solution Approach 2:
Each network node is designed with universal functionality to independently perform validation operations using locally stored information. This multi-functionality eliminates the need for centralized access, allowing any node to handle validation requests efficiently while maintaining data integrity through distributed storage
Data Source
AI summary
A system communicates a request to a plurality of network nodes to provide user information associated with a document. The system receives a plurality of log files that comprises data communications among the network nodes and responses to the request. The system determines a first number of network nodes that are associated with a first anomaly from the plurality of log files. The system determines a second number of network nodes that are associated with a second anomaly from the plurality of log files. The system determines the number of malicious network nodes by combining the first number and the second number of network nodes. If the system determines that the number of malicious network nodes exceeds a threshold percentage, it assigns one or more network nodes to store the user information until the number of malicious network nodes is less than the threshold percentage.