Supply chain management with secured data transmission via improved DNA cryptosystem

IF 0.2 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Web Intelligence Pub Date : 2023-12-12 DOI:10.3233/web-230105

P. Lahane, Shivaji R. Lahane

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引用次数: 0

Abstract

Supply chain management (SCM) is most significant place of concentration in various corporate circumstances. SCM has both designed and monitored numerous tasks with the following phases such as allocation, creation, product sourcing, and warehousing. Based on this perspective, the privacy of data flow is more important among producers, suppliers, and customers to ensure the responsibility of the market. This work aims to develop a novel Improved Digital Navigator Assessment (DNA)-based Self Improved Pelican Optimization Algorithm (IDNA-based SIPOA model) for secured data transmission in SCM via blockchain. An improved DNA cryptosystem is done for the process of preservation for data. The original message is encrypted by Improved Advanced Encryption Standard (IAES). The optimal key generation is done by the proposed SIPOA algorithm. The efficiency of the adopted model has been analyzed with conventional methods with regard to security for secured data exchange in SCM. The proposed IDNA-based SIPOA obtained the lowest value for the 40% cypher text is 0.71, while the BWO is 0.79, DOA is 0.77, TWOA is 0.84, BOA is 0.83, POA is 0.86, SDSM is 0.88, DNASF is 0.82 and FSA-SLnO is 0.78, respectively.

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通过改进的 DNA 密码系统进行安全数据传输的供应链管理

供应链管理（SCM）是各种企业环境中最重要的集中地。供应链管理的设计和监控任务繁多，包括分配、创建、产品采购和仓储等阶段。从这个角度看，数据流在生产商、供应商和客户之间的私密性对确保市场责任更为重要。这项工作旨在开发一种新颖的基于改进数字导航评估（DNA）的自改进鹈鹕优化算法（基于 IDNA 的 SIPOA 模型），通过区块链实现供应链管理中的安全数据传输。在数据保存过程中使用了改进的 DNA 密码系统。原始信息由改进高级加密标准（IAES）加密。最佳密钥生成由建议的 SIPOA 算法完成。在单片机安全数据交换的安全性方面，对所采用模型的效率与传统方法进行了分析。所提出的基于 IDNA 的 SIPOA 算法获得的 40% 加密文本的最低值为 0.71，而 BWO 为 0.79，DOA 为 0.77，TWOA 为 0.84，BOA 为 0.83，POA 为 0.86，SDSM 为 0.88，DNASF 为 0.82，FSA-SLnO 为 0.78。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Web Intelligence COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

0.90

自引率

0.00%

发文量

期刊介绍： Web Intelligence (WI) is an official journal of the Web Intelligence Consortium (WIC), an international organization dedicated to promoting collaborative scientific research and industrial development in the era of Web intelligence. WI seeks to collaborate with major societies and international conferences in the field. WI is a peer-reviewed journal, which publishes four issues a year, in both online and print form. WI aims to achieve a multi-disciplinary balance between research advances in theories and methods usually associated with Collective Intelligence, Data Science, Human-Centric Computing, Knowledge Management, and Network Science. It is committed to publishing research that both deepen the understanding of computational, logical, cognitive, physical, and social foundations of the future Web, and enable the development and application of technologies based on Web intelligence. The journal features high-quality, original research papers (including state-of-the-art reviews), brief papers, and letters in all theoretical and technology areas that make up the field of WI. The papers should clearly focus on some of the following areas of interest: a. Collective Intelligence[...] b. Data Science[...] c. Human-Centric Computing[...] d. Knowledge Management[...] e. Network Science[...]

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