Blockchain Pattern Recognition via Hash-Linked Data Signatures
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Solution Overview
Problem
Traditional blockchain systems lack the ability to identify patterns in real-time while maintaining the integrity and security of the blockchain, which is crucial for detecting malicious network activities such as repeated attempts from the same source or simultaneous requests from different sources.
Innovation Solution
A blockchain system that detects patterns in network activity by creating a hash-linked chain of blocks, where each subsequent block includes a hash of the request data from the previous block, allowing for the recognition and storage of patterns within the blockchain, enabling real-time pattern detection and secure logging of router activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional blockchain systems store all transaction data, then data integrity is maintained, but the system cannot efficiently detect patterns in real-time
Solution Approach 1:
The patent extracts only essential data attributes from transactions to create pattern signatures, rather than storing and analyzing complete transaction data. This allows the system to maintain data integrity through blockchain's immutable ledger while improving pattern detection efficiency by working with condensed signature representations.
Solution Approach 2:
The patent segments transactions into distinct data attributes (source, destination, amount, timestamp) and creates separate signature components for each attribute type. This segmentation enables efficient pattern matching by comparing individual attribute signatures rather than analyzing entire transaction records.
2Reliability
If the blockchain system monitors all network requests, then malicious patterns can be detected, but network performance and throughput are degraded
Solution Approach 1:
The system extracts only critical data attributes from network requests (source address, destination address, transaction type) to create compact signatures. This extraction approach enables security monitoring without processing complete request data, thereby maintaining network throughput while detecting malicious patterns.
Solution Approach 2:
The system performs preliminary pattern matching by comparing signature components against known malicious patterns before full transaction processing. This preliminary action enables early detection of suspicious activity without blocking legitimate network traffic, maintaining both security and performance.
3Measurement precision
If pattern detection is performed on complete transaction data, then accurate pattern recognition is achieved, but computational resources are consumed
Solution Approach 1:
The patent extracts essential pattern-defining attributes from complete transactions to create signatures. This extraction maintains pattern recognition accuracy by focusing on the most discriminative features while significantly reducing computational resource consumption by avoiding processing of redundant data.
Solution Approach 2:
The system performs partial pattern matching by comparing only signature components rather than complete transaction data. This partial action approach achieves sufficient pattern recognition accuracy for security purposes while consuming far fewer computational resources than full data analysis.
Data Source
AI summary
An example operation may include one or more of a network interface configured to receive requests transmitted from client devices, each request comprising a plurality of data attributes, a processor configured to detect a pattern from within the received requests, the detected pattern comprising a plurality of requests that share one or more data attributes in common and a storage configured to store the detected pattern as a hash-linked chain of blocks within a blockchain, wherein the hash-linked chain of blocks comprises a sequence of blocks corresponding to a sequence of the plurality of requests included in the detected pattern, and, after the first block, each subsequent block in the hash-linked chain of blocks includes a hash of request data that is stored in a previous block.