NEXT-GENERATION ENCRYPTION METHODS FOR SECURE CLOUD DATA STORAGE

In the era of cloud computing and big data, ensuring secure and efficient data storage is paramount. Storage Area Networks (SAN) play a critical role in providing high-speed data access; however, they face significant challenges related to time complexity in encryption processes. Traditional encryption methods often compromise performance, leading to increased latency and inefficiencies. This study addresses these issues by proposing an Enhanced Homomorphic Encryption (EHE) model that integrates a camouflage process and a substitution-based key generation method. The EHE model not only enhances data security but also optimizes encryption and decryption times. Experimental results reveal that EHE significantly outperforms both RivestShamir-Adleman (RSA) and standard Homomorphic Encryption (HE) techniques, achieving a processing time reduction of 11 seconds compared to 12 seconds for RSA and 250 seconds for HE. This research underscores the need for advanced encryption methodologies in modern computing environments and recommends further exploration of EHE’s applications in various data security contexts.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-05
DOI
https://doi.org/10.5281/zenodo.17531711
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
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article

NEXT-GENERATION ENCRYPTION METHODS FOR SECURE CLOUD DATA STORAGE

Zenodo (CERN European Organization for Nuclear Research)
Cryptography and Data Security
article

NEXT-GENERATION ENCRYPTION METHODS FOR SECURE CLOUD DATA STORAGE

article en

Abstract

In the era of cloud computing and big data, ensuring secure and efficient data storage is paramount. Storage Area Networks (SAN) play a critical role in providing high-speed data access; however, they face significant challenges related to time complexity in encryption processes. Traditional encryption methods often compromise performance, leading to increased latency and inefficiencies. This study addresses these issues by proposing an Enhanced Homomorphic Encryption (EHE) model that integrates a camouflage process and a substitution-based key generation method. The EHE model not only enhances data security but also optimizes encryption and decryption times. Experimental results reveal that EHE significantly outperforms both RivestShamir-Adleman (RSA) and standard Homomorphic Encryption (HE) techniques, achieving a processing time reduction of 11 seconds compared to 12 seconds for RSA and 250 seconds for HE. This research underscores the need for advanced encryption methodologies in modern computing environments and recommends further exploration of EHE’s applications in various data security contexts.

Zenodo (CERN European Organization for Nuclear Research)
Rivers State University (NG)
Openalex Percentile: Top 23%
Cryptography and Data Security
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