A New Framework for Securing Personal Data Using the Multi-Cloud

Relaying On A Single Cloud As A Storage Service Is Not A Proper Solution For A Number Of Reasons; For Instance, The Data Could Be Captured While Uploaded To The Cloud, And The Data Could Be Stolen From The Cloud Using A Stolen Id. In This Paper, We Propose A Solution That Aims At Offering A Secure Data Storage For Mobile Cloud Computing Based On The Multi-Clouds Scheme. The Proposed Solution Will Take The Advantages Of Multi-Clouds, Data Cryptography, And Data Compression To Secure The Distributed Data; By Splitting The Data Into Segments, Encrypting The Segments, Compressing The Segments, Distributing The Segments Via Multi-Clouds While Keeping One Segment On The Mobile Device Memory; Which Will Prevent Extracting The Data If The Distributed Segments Have Been Intercepted.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-27
DOI
https://doi.org/10.5281/zenodo.16962364
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

A New Framework for Securing Personal Data Using the Multi-Cloud

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

A New Framework for Securing Personal Data Using the Multi-Cloud

article en

Abstract

Relaying On A Single Cloud As A Storage Service Is Not A Proper Solution For A Number Of Reasons; For Instance, The Data Could Be Captured While Uploaded To The Cloud, And The Data Could Be Stolen From The Cloud Using A Stolen Id. In This Paper, We Propose A Solution That Aims At Offering A Secure Data Storage For Mobile Cloud Computing Based On The Multi-Clouds Scheme. The Proposed Solution Will Take The Advantages Of Multi-Clouds, Data Cryptography, And Data Compression To Secure The Distributed Data; By Splitting The Data Into Segments, Encrypting The Segments, Compressing The Segments, Distributing The Segments Via Multi-Clouds While Keeping One Segment On The Mobile Device Memory; Which Will Prevent Extracting The Data If The Distributed Segments Have Been Intercepted.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 63%
Geochemistry and Geologic Mapping
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