Blockchain Assisted Secure Data Sharing Model for Internet of Things Based Smart Industries

ASIAIR > College of Computer Science > Department of Computer Science and Information Engineering > Journal Artical > Item 310904400/115535

Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/115535

Title:	Blockchain Assisted Secure Data Sharing Model for Internet of Things Based Smart Industries
Authors:	Gunasekaran;Manogaran, Gunasekaran;Alaza, Mamoun;Alazab, Mamoun;P, Mohamed S;Shakeel, P. Mohamed;許慶賢;Hsu, Ching-Hsien
Contributors:	資訊電機學院資訊工程學系
Date:	2022-03-01
Issue Date:	2023-03-29 02:32:22 (UTC+0)
Publisher:	亞洲大學
Abstract:	Industrial Internet of Things is focused to improve the performance of smart factories through automation and scalable functions. IoT paradigm, information and communication technology, and intelligent computing are assimilated as a single entity for industrial automation, optimization, sharing and security, and scalability. In a view of the security requirement in smart industry data sharing through IoT, this article introduces a blockchain-assisted secure data sharing (BSDS) model. This model is responsible for administering inbound and outbound security in data acquisition and dissemination. The inbound acquisition is first classified using recurrent learning to identify adverse sequences in data dissemination. In the outbound security measure, end-to-end authentication based on the blockchain information of reputation and sequence differentiation is engaged. The blockchain paradigm controls the data gathering and dissemination instances through the classification and integrity verification in both the industry and processing terminals. For this purpose, the functions of the blockchain are riven for data gathering and monitoring in the smart industry whereas integrity and sequence verification is performed by the nonmining blockchain terminal in the processing environment. The integrated security measures are capable of maximizing the response rate by confining false alarm progression, failure rate, and time delay. Statistical analysis shows that the BSDS achieves a 5.67% high response rate and reduces the failure rate by 2.14%. Further, it achieves 3.12%, maximizes response rate by 6.63%, and reduces delay by 11.91%, respectively.
Appears in Collections:	[Department of Computer Science and Information Engineering] Journal Artical

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	123	View/Open

Loading...