Blockchain Attack Detection Using Chain Splits and Proof of Invalidity
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Solution Overview
Problem
Existing blockchain technologies are vulnerable to sophisticated security attacks, such as double-spending and transaction withholding, and fail to capture coalitions and deviations from honest behavior, leading to compromised network security and efficiency.
Innovation Solution
A system and method for detecting and neutralizing security attacks in blockchain networks by using a transaction inclusion protocol to validate transactions, initiating a split in the blockchain when a height threshold is breached, and adding a proof of invalidity (POI) to invalidate adversary blockchains, thereby disincentivizing attacks through rational user behavior and network fairness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing blockchain methods use Proof of Work consensus algorithm, then decentralized security and transaction validation are achieved, but the system becomes vulnerable to sophisticated security attacks such as double-spending and transaction withholding
Solution Approach 1:
The system performs preliminary validation of transactions against multiple attack vectors before they are committed to the blockchain. The transaction inclusion protocol checks for double-spending attempts, transaction withholding patterns, and coalition-based attacks in advance, preventing harmful actions before they can compromise security.
Solution Approach 2:
The system implements continuous monitoring and feedback mechanisms that detect abnormal behavior patterns in real-time. When suspicious transactions are detected, the system provides feedback to validate or reject them, and adjusts consensus validation parameters dynamically to counter emerging attack strategies while maintaining secure operation.
2Reliability
If the blockchain network validates transactions through strict consensus protocols, then network security is maintained, but transaction processing speed decreases
Solution Approach 1:
The system applies partial validation actions for transactions that pass preliminary checks, reducing the computational overhead for legitimate transactions while maintaining full security validation for suspicious ones. This selective validation approach maintains network security without unnecessarily slowing down routine transaction processing.
Solution Approach 2:
The validation protocol dynamically adjusts its strictness based on network conditions and detected attack patterns. During normal operation, the system uses lighter validation rules to improve throughput, but automatically increases validation strictness when attack vectors are detected, balancing security and productivity adaptively.
3Device complexity
If existing blockchain methods assume rational miner behavior, then game theory analysis simplifies the model, but the system fails to capture coalitions and deviations from honest behavior
Solution Approach 1:
The system segments the miner population into distinct behavioral categories (honest miners, rational miners, and adversarial miners) and applies different validation rules and monitoring strategies to each group. This segmentation allows the system to handle complex coalition behaviors and deviations without overwhelming complexity in the overall game theory model.
Solution Approach 2:
The system changes key parameters in the game theory model dynamically based on observed miner behavior. When coalitional behavior or deviations from rationality are detected, the system adjusts payoff parameters, validation thresholds, and consensus rules to accommodate these behavioral changes while maintaining model manageability and security.
4Reliability
If the blockchain network implements comprehensive security validation, then attack resistance is improved, but network fairness and consensus efficiency are compromised
Solution Approach 1:
The system applies different validation qualities to different parts of the transaction pool. Transactions that pass initial heuristic checks receive standard validation, while those flagged as suspicious receive enhanced validation. This local differentiation maintains attack resistance without uniformly slowing down the entire consensus process, preserving network fairness.
Data Source
AI summary
The present disclosure provides a system for detecting and neutralizing a plurality of security attacks on a blockchain network to improve security of the blockchain network. The system includes a sender node that is configured to send a transaction to a user device associated with at least one user. The blockchain network is configured to (i) receive the transaction from the sender node when the first block gets validated in the first blockchain, (ii) validate the transaction of the first block to neutralize the first attack, (iii) determine a second attack by initiating a split in the first blockchain to determine a second blockchain, and (iv) invalidate the second blockchain when the latest block of the first blockchain invalidates the second block of the second blockchain when a proof of invalidity (POI) is added to the second block to neutralize the second attack.