{"title":"An Efficient Reconfigurable Cryptographic Model for Dynamic and Secure Unstructured Data Sharing in Multi-Cloud Storage Server","authors":"Parashiva Murthy Basavanapura Muddumadappa, Sumithra Devi Kengeri Anjanappa, Mallikarjunaswamy Srikantaswamy","doi":"10.56578/jisc010107","DOIUrl":null,"url":null,"abstract":"This study designs a reconfigurable multi-cloud storage server architecture for dynamic and secure data sharing has been designed, improves the security of unstructured data using cryptographic index-based data slicing (CIBDS), and reduces the malicious insider through data encryption using a third data encryption algorithm (3DEA). Focusing on multi-cloud storage server (MCSS) and data life cycle which includes three stages (i.e., data input, transition and utilization), the authors determined the efficiency of reconfigurable data file slicing, standard format, privacy and trustworthiness of the customers, in contrast to existing methods. Every part of a data file was encrypted using 3DEA, and Rivest Shamir Adleman (RSA) was employed to produce the private key to secure the unstructured data. The results show that the proposed framework effectively searches the data files in MCSS based on tags, such as input file names and private keys. The performance of the framework was measured by the security level, uploading/downloading latency time between our method and conventional methods, under different data sizes in (MB). Overall, our method reduces the malicious insider to 0.23% using 3DEA and RSA, during data encryption in the existing USDS-MC, shortens the uploading/downloading latency time (s) by 10% and 12%, compared to USDS-MC, and enhances the unstructured data security by 12% in comparison with that method. In this way, the authors managed to improve the self-protection of reconfigurable and secure unstructured data files in huge cloud infrastructure. This research optimizes the data security and privacy of encryption, decryption and cryptography technologies, and helps with the online process and its security maintenance during cloud storage.","PeriodicalId":272946,"journal":{"name":"Journal of Intelligent Systems and Control","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Intelligent Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56578/jisc010107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This study designs a reconfigurable multi-cloud storage server architecture for dynamic and secure data sharing has been designed, improves the security of unstructured data using cryptographic index-based data slicing (CIBDS), and reduces the malicious insider through data encryption using a third data encryption algorithm (3DEA). Focusing on multi-cloud storage server (MCSS) and data life cycle which includes three stages (i.e., data input, transition and utilization), the authors determined the efficiency of reconfigurable data file slicing, standard format, privacy and trustworthiness of the customers, in contrast to existing methods. Every part of a data file was encrypted using 3DEA, and Rivest Shamir Adleman (RSA) was employed to produce the private key to secure the unstructured data. The results show that the proposed framework effectively searches the data files in MCSS based on tags, such as input file names and private keys. The performance of the framework was measured by the security level, uploading/downloading latency time between our method and conventional methods, under different data sizes in (MB). Overall, our method reduces the malicious insider to 0.23% using 3DEA and RSA, during data encryption in the existing USDS-MC, shortens the uploading/downloading latency time (s) by 10% and 12%, compared to USDS-MC, and enhances the unstructured data security by 12% in comparison with that method. In this way, the authors managed to improve the self-protection of reconfigurable and secure unstructured data files in huge cloud infrastructure. This research optimizes the data security and privacy of encryption, decryption and cryptography technologies, and helps with the online process and its security maintenance during cloud storage.