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.
In this paper an efficient secure cloud computing framework has been developed. This framework consists of data grouping based on fuzzy c-means (FCM). It has been used for the individual and associative rankings of uploaded text data on the cloud. For the decision selection ranking of the data simple additive weighting (SAW) method have been used. For data security RC6, RSA and AES algorithms have been used collectively and individually based on the condition. RC6, AES and RSA algorithms have been used as a combination for the complex key security. Based on the decision performance rankingtop higher rank which supports are >=50% adopted all the three security algorithms, only one key is applied for the remaining data. The maximum number of keys applied is 5 but there are total three key variants mainly applicable. So we have considered three keys. It has been clear from our results that the keys spreading are automatically increased on the basis of number of files. So in case of high risk the keys are increased automatically and applied.
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