Open Access
ARTICLE
An Effective Non-Commutative Encryption Approach with Optimized Genetic Algorithm for Ensuring Data Protection in Cloud Computing
S. Jerald Nirmal Kumar1,*, S. Ravimaran2, M. M. Gowthul Alam3
1 Anna University, Chennai, 600025, India
2 M.A.M College of Engineering, Trichy, 621105, India
3 Sethu Institute of Technology, Virudhunagar, 626115, India
* Corresponding Author: S. Jerald Nirmal Kumar. Email:
Computer Modeling in Engineering & Sciences 2020, 125(2), 671-697. https://doi.org/10.32604/cmes.2020.09361
Received 06 December 2019; Accepted 24 August 2020; Issue published 12 October 2020
Abstract
Nowadays, succeeding safe communication and protection-sensitive
data from unauthorized access above public networks are the main worries
in cloud servers. Hence, to secure both data and keys ensuring secured data
storage and access, our proposed work designs a Novel Quantum Key Distribution (QKD) relying upon a non-commutative encryption framework. It
makes use of a Novel Quantum Key Distribution approach, which guarantees high level secured data transmission. Along with this, a shared secret
is generated using Diffie Hellman (DH) to certify secured key generation at
reduced time complexity. Moreover, a non-commutative approach is used,
which effectively allows the users to store and access the encrypted data
into the cloud server. Also, to prevent data loss or corruption caused by
the insiders in the cloud, Optimized Genetic Algorithm (OGA) is utilized,
which effectively recovers the data and retrieve it if the missed data without
loss. It is then followed with the decryption process as if requested by the
user. Thus our proposed framework ensures authentication and paves way
for secure data access, with enhanced performance and reduced complexities
experienced with the prior works.
Keywords
Cite This Article
Jerald, S., Ravimaran, S., M., M. (2020). An Effective Non-Commutative Encryption Approach with Optimized Genetic Algorithm for Ensuring Data Protection in Cloud Computing.
CMES-Computer Modeling in Engineering & Sciences, 125(2), 671–697.
Citations