An Efficient Secure Data Deduplication and Portability in Distributed Cloud Server Using Whirlpool-Hct and Lf-Wdo

Abstract

In accordance with the application or file environment or data, the Data Owners (DOs) can
store their data remotely with the aid of a service being developed termed Distributed Cloud
Computing (DCC) storage. Nevertheless, the trustworthiness of the user to amass data is broken
by certain issues of Distributed Cloud Storage (DCS) like higher uploading bandwidth,
insecure data storage, along with integration issues. A Data De-duplication (DD) along with
portability-centered secure data storage in DCS is developed here to overcome the
aforementioned challenges. Here, by utilizing the Gaussian Kernel –Quadratic Discriminate
Analysis (GK-QDA) Feature Reduction Methodology together with Hybrid Forest Genetic
(HFG) Feature selection technique, the unwanted data are removed and the relevant features
are selected to prevent data loss. By employing a whirlpool hashing algorithm in conjunction
with a hash chaining algorithm, the cloud server being selected for the corresponding data or
application is evaluated for data redundancy by data duplication. At last, a Levy Flight – Wind
Driven Optimization (LF-WDO) Algorithm is developed here to mitigate the integration
problems whilst moving the encrypted data betwixt the DCS. The experiential evaluation
displayed that the proposed model performs better than the prevailing methodologies by
attaining a computation time of 2987 ms.