{"title":"通过改进的 DNA 密码系统进行安全数据传输的供应链管理","authors":"P. Lahane, Shivaji R. Lahane","doi":"10.3233/web-230105","DOIUrl":null,"url":null,"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.","PeriodicalId":42775,"journal":{"name":"Web Intelligence","volume":"36 10","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Supply chain management with secured data transmission via improved DNA cryptosystem\",\"authors\":\"P. Lahane, Shivaji R. Lahane\",\"doi\":\"10.3233/web-230105\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":42775,\"journal\":{\"name\":\"Web Intelligence\",\"volume\":\"36 10\",\"pages\":\"\"},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2023-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Web Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/web-230105\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Web Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/web-230105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Supply chain management with secured data transmission via improved DNA cryptosystem
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.
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[...]