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Enhancing Blockchain Security Using Ripple Consensus Algorithm

A. Baseera1, Abeer Abdullah Alsadhan2,*

1 School of Computing Science and Engineering, VIT Bhopal University, Bhopal, 466114, India
2 Department of Computer Science, Imam Abdulrahman Bin Faisal University, Dammam, 34212, Saudi Arabia

* Corresponding Author: Abeer Abdullah Alsadhan. Email: email

Computers, Materials & Continua 2022, 73(3), 4713-4726. https://doi.org/10.32604/cmc.2022.029538

Abstract

In the development of technology in various fields like big data analysis, data mining, big data, cloud computing, and blockchain technology, security become more constrained. Blockchain is used in providing security by encrypting the sharing of information. Blockchain is applied in the peer-to-peer (P2P) network and it has a decentralized ledger. Providing security against unauthorized breaches in the distributed network is required. To detect unauthorized breaches, there are numerous techniques were developed and those techniques are inefficient and have poor data integrity. Hence, a novel technique needs to be implemented to tackle the new breaches in the distributed network. This paper, proposed a hybrid technique of two fish with a ripple consensus algorithm (TF-RC). To improve the detection time and security, this paper uses efficient transmission of data in the distributed network. The experimental analysis of TF-RC by using the metric measures of performance in terms of latency, throughput, energy efficiency and it produced better performance.

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Cite This Article

APA Style
Baseera, A., Alsadhan, A.A. (2022). Enhancing blockchain security using ripple consensus algorithm. Computers, Materials & Continua, 73(3), 4713-4726. https://doi.org/10.32604/cmc.2022.029538
Vancouver Style
Baseera A, Alsadhan AA. Enhancing blockchain security using ripple consensus algorithm. Comput Mater Contin. 2022;73(3):4713-4726 https://doi.org/10.32604/cmc.2022.029538
IEEE Style
A. Baseera and A.A. Alsadhan, "Enhancing Blockchain Security Using Ripple Consensus Algorithm," Comput. Mater. Contin., vol. 73, no. 3, pp. 4713-4726. 2022. https://doi.org/10.32604/cmc.2022.029538



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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