Secure keys data distribution based user-storage-transit server authentication process model using mathematical post-quantum cryptography methodology

3Citations
Citations of this article
51Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The central remote servers are essential for storing and processing data for cloud computing evaluation. However, traditional systems need to improve their ability to provide technical data security solutions. Many data security challenges and complexities await technical solutions in today’s fast-growing technology. These complexities will not be resolved by combining all secure encryption techniques. Quantum computing efficiently evolves composite algorithms, allowing for natural advances in cyber security, forensics, artificial intelligence, and machine learning-based complex systems. It also demonstrates solutions to many challenging problems in cloud computing security. This study proposes a user-storage-transit-server authentication process model based on secure keys data distribution and mathematical post-quantum cryptography methodology. The post-quantum cryptography mathematical algorithm is used in this study to involve the quantum computing-based distribution of security keys. It provides security scenarios and technical options for securing data in transit, storage, user, and server modes. Post-quantum cryptography has defined and included the mathematical algorithm in generating the distributed security key and the data in transit, on-storage, and on-editing. It has involved reversible computations on many different numbers by super positioning the qubits to provide quantum services and other product-based cloud-online access used to process the end-user’s artificial intelligence-based hardware service components. This study will help researchers and industry experts prepare specific scenarios for synchronizing data with medicine, finance, engineering, and banking cloud servers. The proposed methodology is implemented with single-tenant, multi-tenant, and cloud-tenant-level servers and a database server. This model is designed for four enterprises with 245 users, and it employs integration parity rules that are implemented using salting techniques. The experimental scenario considers the plain text size ranging from 24 to 8248 for analyzing secure key data distribution, key generation, encryption, and decryption time variations. The key generation and encryption time variations are 2.3233 ms to 8.7277 ms at quantum-level 1 and 0.0355 ms to 1.8491 ms at quantum-level 2. The key generation and decryption time variations are 2.1533 ms to 19.4799 ms at quantum-level 1 and 0.0525 ms to 3.3513 ms at quantum-level 2.

References Powered by Scopus

Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer

5509Citations
N/AReaders
Get full text

Unconditional security of quantum key distribution over arbitrarily long distances

1466Citations
N/AReaders
Get full text

Advances in quantum cryptography

1194Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Improving Digital Forensic Security: A Secure Storage Model With Authentication and Optimal Key Generation Based Encryption

2Citations
N/AReaders
Get full text

Multi-layered access control based auto tuning relational key implications in enterprise-level multi-tenancy

0Citations
N/AReaders
Get full text

Secure data encryption key scenario for protecting private data security and privacy

0Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Henge, S. K., Jayaraman, G., Sreedevi, M., Rajakumar, R., Rashid, M., Alshamrani, S. S., … Alghamdi, A. S. (2023). Secure keys data distribution based user-storage-transit server authentication process model using mathematical post-quantum cryptography methodology. Networks and Heterogeneous Media, 18(3), 1313–1334. https://doi.org/10.3934/NHM.2023057

Readers over time

‘23‘24‘2509182736

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 5

38%

Professor / Associate Prof. 3

23%

Researcher 3

23%

Lecturer / Post doc 2

15%

Readers' Discipline

Tooltip

Engineering 6

40%

Computer Science 4

27%

Business, Management and Accounting 4

27%

Social Sciences 1

7%

Save time finding and organizing research with Mendeley

Sign up for free
0