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A Novel High-Efficiency Transaction Verification Scheme for Blockchain Systems

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摘要 Blockchain can realize the reliable storage of a large amount of data that is chronologically related and verifiable within the system.This technology has been widely used and has developed rapidly in big data systems across various fields.An increasing number of users are participating in application systems that use blockchain as their underlying architecture.As the number of transactions and the capital involved in blockchain grow,ensuring information security becomes imperative.Addressing the verification of transactional information security and privacy has emerged as a critical challenge.Blockchain-based verification methods can effectively eliminate the need for centralized third-party organizations.However,the efficiency of nodes in storing and verifying blockchain data faces unprecedented challenges.To address this issue,this paper introduces an efficient verification scheme for transaction security.Initially,it presents a node evaluation module to estimate the activity level of user nodes participating in transactions,accompanied by a probabilistic analysis for all transactions.Subsequently,this paper optimizes the conventional transaction organization form,introduces a heterogeneous Merkle tree storage structure,and designs algorithms for constructing these heterogeneous trees.Theoretical analyses and simulation experiments conclusively demonstrate the superior performance of this scheme.When verifying the same number of transactions,the heterogeneous Merkle tree transmits less data and is more efficient than traditional methods.The findings indicate that the heterogeneous Merkle tree structure is suitable for various blockchain applications,including the Internet of Things.This scheme can markedly enhance the efficiency of information verification and bolster the security of distributed systems.
出处 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第5期1613-1633,共21页 工程与科学中的计算机建模(英文)
基金 funded by the National Natural Science Foundation of China(62072056,62172058) the Researchers Supporting Project Number(RSP2023R102)King Saud University,Riyadh,Saudi Arabia funded by the Hunan Provincial Key Research and Development Program(2022SK2107,2022GK2019) the Natural Science Foundation of Hunan Province(2023JJ30054) the Foundation of State Key Laboratory of Public Big Data(PBD2021-15) the Young Doctor Innovation Program of Zhejiang Shuren University(2019QC30) Postgraduate Scientific Research Innovation Project of Hunan Province(CX20220940,CX20220941).
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