An Empirical Client Cloud Environment to Secure Data Communication with Alert Protocol. (21st September 2022)

• Record Type: Journal Article
• Authors: Soni, Dheresh; Srivastava, Deepak; Bhatt, Ashutosh; Aggarwal, Ambika; Kumar, Sunil; Shah, Mohd Asif
• Other Names: El Kafhali Said Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2022(2022)
• Publication Date: 2022-09-21
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2022/4696649
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Cloud computing is a technology that provides resources and utility services based on user demand. Due to this demand, efficient cloud security protocols are highly required, especially at the time of data communication for user authentication and data aggregation. The data communication scenarios are majorly affected by the security threats in the cloud computing environment. This article provides a practical approach to developing an efficient and empirical cloud framework in terms of cloud protocol. The framework uses fuzzy c-means (FCM) algorithm to group data, and calculation is done individually or associatively to rank the text data. Uploaded data are passed to a simple additive weighting (SAW) algorithm for ranking and making decision selection. The framework executes in three phases, namely data preprocessing, clustering, and automatic data security with an alert mechanism. The process is completely automated so there is no need of considering the individual files for the processing and the data held will be appropriately correlated with the sharing inter-cloud environment. To inspect security issues, the proposed framework is secured by three different security algorithms. The encryption process is completed by Rivest Cipher 6 (RC6); the substitution process is done by Advanced Encryption Standard (AES); and key generation is done by RC6, AES, and Rivest-Shamir-Adleman (RSA) approaches collectively. Based on the given situations, these standard approaches were automatically applied separately or collectively. Unauthorized access trapping and data deletion mechanism are also provided in the proposed framework. The experimental results with a comparative study depicted the effectiveness of the proposed work.