{"title":"Fusion-based advanced encryption algorithm for enhancing the security of Big Data in Cloud","authors":"A. Vidhya, P. M. Kumar","doi":"10.1177/1063293X221089086","DOIUrl":null,"url":null,"abstract":"Every organization in this digital age is expected to exponentially increase its digital data due to generations from machines. The advanced computations of Big Data are now showing various opportunities for the researchers who work on security enhancements to ensure the efficient accessibility of the data stores. Our research work aims to derive a Fusion-based Advanced Encryption Algorithm (FAEA) for a cost-optimized satisfiable security model toward the usage of Big Data in the cloud. The FAEA method is evaluated for its performance toward efficiency, scalability, and security and proved to be 98% ahead of the existing methods of Security Hadoop Distributed File System Sec (HDFS) and Map Reduce Encryption Scheme (MRE). On the other hand, this work aims to address the problems of usage of Big Data in the cloud toward the sole solution, cost-effective solutioning, and proof of ownership. The outcome analysis of FAEA revolves around addressing these three major problems. This research work would be much helpful for the IT industries to manage Big Data in Cloud with security aspects for the decade.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"81 1","pages":"171 - 180"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Concurrent Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1063293X221089086","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Every organization in this digital age is expected to exponentially increase its digital data due to generations from machines. The advanced computations of Big Data are now showing various opportunities for the researchers who work on security enhancements to ensure the efficient accessibility of the data stores. Our research work aims to derive a Fusion-based Advanced Encryption Algorithm (FAEA) for a cost-optimized satisfiable security model toward the usage of Big Data in the cloud. The FAEA method is evaluated for its performance toward efficiency, scalability, and security and proved to be 98% ahead of the existing methods of Security Hadoop Distributed File System Sec (HDFS) and Map Reduce Encryption Scheme (MRE). On the other hand, this work aims to address the problems of usage of Big Data in the cloud toward the sole solution, cost-effective solutioning, and proof of ownership. The outcome analysis of FAEA revolves around addressing these three major problems. This research work would be much helpful for the IT industries to manage Big Data in Cloud with security aspects for the decade.