HTLC Cross-Chain Transaction Tracking via Secret Hash Analysis
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Solution Overview
Problem
Managing transactions across multiple blockchain networks is challenging due to the difficulty in identifying associated transactions and deriving hidden information, particularly in cross-chain transactions, which are often implicit and difficult for financial institutions to track.
Innovation Solution
A computer-implemented method that identifies Hash Time Locked Contract (HTLC) transactions across different blockchain networks by comparing transaction commit times, secret hashes, and expiration times, and derives hidden information such as exchange ratios and parties involved through data mining and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If distributed ledger systems are used to securely store data in blockchain networks, then data immutability and security are improved, but the ability to identify and track associated transactions across multiple networks deteriorates
Solution Approach 1:
The patent introduces an intermediary system that acts as a mediator between multiple blockchain networks. This system collects transaction data from different networks, processes it centrally, and identifies cross-chain relationships by comparing secret hashes and timing information. The intermediary enables transaction tracking across networks without compromising the security and immutability of the underlying blockchain systems.
Solution Approach 2:
The patent creates a universal transaction analysis system that can handle multiple types of blockchain networks (public, private, consortium) simultaneously. The system performs multiple functions including data collection, transaction matching, relationship identification, and cross-chain transaction detection within a single platform, enabling broad applicability across different blockchain ecosystems.
2Productivity
If atomic swaps are used to trade assets across different blockchain networks without intermediaries, then transaction efficiency and decentralization are improved, but the ability to identify and supervise customer activities deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where transaction data from multiple blockchain networks is continuously collected and analyzed. The system uses secret hash matching and timing analysis to identify cross-chain transactions, providing feedback loops that enable ongoing supervision of customer activities while maintaining the efficiency of atomic swaps. This allows financial institutions to monitor transactions without directly interfering in the decentralized swap process.
3Adaptability or versatility
If multiple blockchain networks are used for cross-chain transactions, then system versatility and functionality are improved, but the complexity of managing and identifying related transactions increases
Solution Approach 1:
The patent segments the complex task of cross-chain transaction management into distinct components: data collection from individual networks, secret hash extraction, timing information analysis, and relationship matching. By dividing the system into these modular segments, each handling a specific aspect of transaction identification, the overall complexity is reduced while maintaining the ability to manage multiple blockchain networks effectively.
Data Source
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AI summary
Disclosed herein are methods, systems, and apparatus, including computer programs encoded on computer storage media, for managing transactions in blockchain networks. One of the methods includes identifying a first Hash Time Locked Contract (HTLC) transaction in a first blockchain network that is associated with a second HTLC transaction in a second blockchain network different from the first blockchain network, identifying a third HTLC transaction in the second blockchain network that is associated with the second HTLC transaction, identifying a fourth HTLC transaction in the first blockchain network that is associated with the first, second, and third HTLC transactions, the first, second, third, and fourth HTLC transactions being related to a cross-chain transaction across the first and second blockchain networks, and deriving hidden information of the cross-chain transaction from information of the first, second, third, and fourth HTLC transactions based on associations of the first, second, third and fourth HTLC transactions.