Constructive system for double-spend data detection and prevention in inter and intra-block of blockchain
by J. Vijayalakshmi; A. Murugan
International Journal of Computational Science and Engineering (IJCSE), Vol. 24, No. 6, 2021

Abstract: Currently, our global financial market faces lots of trouble due to migration from fiat currency to cryptocurrency and its underlying blockchain technology. Blockchain provides trust in a decentralised way for storing, managing, and retrieving the transactions. The double-spending issue arises due to the erroneous transaction verification mechanism in the blockchain. Research has shown that transaction malleability like double-spending creates millions of bitcoins losses to the owners as well as few bitcoin exchanges. This research aims to detect and prevent the double-spending of bitcoins in single and multiple blocks. In this context, double-spend data in a single block is identified using the DPL2A method. Further, the original transaction from the double-spend transaction list is identified using the ACRT method which acts as a prevention of double-spend in a forthcoming occurrence. Similarly, double-spend data in multiple blocks are identified using MBDTD along with the Cognizant Merkle tree. Finally, a system named F2DP is constructed to detect and prevent the double-spend data in inter and intra blocks of the blockchain. The result indicates these methods will act best for double-spend detection and prevention with a limited set of transaction records. Further research is needed to increase the scalability of transaction records.

Online publication date: Tue, 04-Jan-2022

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