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  Published Paper Details:

  Paper Title

Handling the uncertainty and Noise in Compressed Cloud data storage using Data Science Tools-An Analytical survey

  Authors

  Arafath Hassan.S,  Dr.M.Mohamed Sirajudeen

  Keywords

Data Science Cloud, data, storage and compression.

  Abstract


Data Science tools such as MATLAB, Big ML are used to handling the uncertainty and noise in compressed cloud data storage at different accessing terminals in web applications. The Cloud computing significantly plays a role in the aspect of effective resource utilization and service consumption. Irrespective of the type of clouds (ex. Private, public, hybrid or inter-cloud), every service providers concentrates on the data residing in cloud servers. Each and every moment, the researchers and scholars are proposing multiplicity of security algorithms to secure cloud data during the transactions. Most of the cloud data secure algorithms are focusing on the way to secure to cloud data in a single direction by using cryptographic algorithms. In this research paper focuses on a new direction to combine the features of data compression with the cloud data in order handling the way of uncertainty as well as removing noise in compressed cloud data storage.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2403940

  Paper ID - 243962

  Page Number(s) - h898-h903

  Pubished in - Volume 12 | Issue 3 | March 2024

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Arafath Hassan.S,  Dr.M.Mohamed Sirajudeen,   "Handling the uncertainty and Noise in Compressed Cloud data storage using Data Science Tools-An Analytical survey", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 3, pp.h898-h903, March 2024, Available at :http://www.ijcrt.org/papers/IJCRT2403940.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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