1. Blockchain-based multi-malicious double-spending attack blacklist management model.
- Author
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Wang, JunLu, Liu, Qiang, and Song, Baoyan
- Subjects
BLOCKCHAINS ,MINES & mineral resources - Abstract
In recent years, blockchain security issues have attracted widespread attention. Especially in terms of computing power security, when nodes have sufficient computing power, they can arbitrarily tamper with blockchain ledger data. As a huge collection of computing power, the blockchain mining pool is a potential malicious node. Multiple malicious nodes jointly conduct a double-spending attack on the blockchain, which brings great security risks to the blockchain. This paper studies the different combinations of double-spending attack by potential malicious mining pools, constructs a blacklist judgment strategy based on the attack characteristics, and proposes a blockchain-based multi-malicious double-spending attack blacklist management model. Firstly, an inner loop malicious game is proposed to analyze the competition trend between a single malicious node and other malicious nodes. Secondly, according to the attack mode of multiple mining pools, a joint attack model and a decentralized attack model are proposed, and the operation rules of the two attack models are mathematically derived. Then a blacklist management model is proposed, and after the blacklist is constructed, a blacklist judgment strategy is formulated. The blacklist uses decentralize mining pool judgments and joint mining pool judgments to extract malicious mining pool nodes, which stops further malicious behavior. And finally, simulation experiments show that the blacklist management model can significantly reduce the success of attacks and resist double-spending attacks effectively. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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