Cryptographic Solutions for Data Security in Cloud Computing:

A Run Time Trend-based Comparison of NCS, ERSA, and EHS

Authors

  • John Kwao Dawson Computer Science Department, Sunyani Technical University, Sunyani, Ghana
  • Frimpong Twum Computer Science Department, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
  • James Benjamin Hayfron Acquah Computer Science Department, Sunyani Technical University, Sunyani, Ghana
  • Yaw Marfo Missah Computer Science Department, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

DOI:

https://doi.org/10.13052/jcsm2245-1439.1324

Keywords:

Non-deterministic, cryptography, execution time, Encryption, Decryption, throughput

Abstract

Due to the recent explosion in the amount of data being created by various social media platforms, e-commerce websites, and other businesses, a paradigm shift from on-site data centers to the cloud is required. Concerns about privacy and secrecy have been a major obstacle to the mainstream adoption of cloud computing. The best approach to protect the confidentiality and privacy of cloud data is by using cryptographic techniques. Researchers have developed several cryptographic algorithms, but they all have lengthy, linear, predictable, memory-intensive execution times. The performance of the CPU, memory, run-time trend, and throughput of the three cryptographic schemes: Enhanced RSA (ERSA), Non-Deterministic Cryptographic Scheme (NCS), and Enhanced Homomorphic Scheme (EHS) are compared using RAsys. The experiment’s results demonstrated that NCS and EHS produced non-linear and non-deterministic run times. Again, NCS and EHS produced the lowest throughput and memory consumption for text and numeric data types when data sizes of 5n*102(KB(∈1,2,4,10,20,40) were processed. However, ERSA produced a run-time trend that was deterministic, linear, and predictable

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Author Biographies

John Kwao Dawson, Computer Science Department, Sunyani Technical University, Sunyani, Ghana

John Kwao Dawson is a PhD candidate in Computer Science at the Kwame Nkrumah University of Science and Technology. He holds a Master of Philosophy in Information Technology and Bachelor of Education in Information Technology from the Kwame Nkrumah University of Science and Technology and University of Education Winneba, respectively. His area of research is cloud computing, algorithm design, machine learning, artificial intelligence and data and network security.

Frimpong Twum, Computer Science Department, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Frimpong Twum received his BSc (hons.) in Electrical and Electronic Engineering and MSc in Internet and Multimedia Engineering from the London South Bank University, in 2004 and 2007, respectively. He also received his MSc in Information System from the Roehampton University, London, in 2011. He completed his PhD in Computer Science from the KNUST, Ghana, in 2017 with a specialization in Computer Security. He is currently a Senior Lecturer at the Department of Computer Science, KNUST.

James Benjamin Hayfron Acquah, Computer Science Department, Sunyani Technical University, Sunyani, Ghana

James Benjamin Hayfron-Acquah is the Head of the Department of Computer Science. He had his first degree in Computer Science from the Kwame Nkrumah University of Science and Technology (KNUST), in 1991. He then proceeded to have his Master’s in Computer Science and Application at the Shanghai University of Science and Technology (SUST), Shanghai, China, in 1996. He obtained his PhD from the Southampton University in the UK, in 2003. He joined the KNUST in March 1996 as a Lecturer. He was promoted to a Senior Lecturer in 2004 and Associate Professor in 2015.

Yaw Marfo Missah, Computer Science Department, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Yaw Marfo Missah is a Lecturer in the Computer Science Department of Kwame Nkrumah University of Science and Technology. He obtained his PhD in Computer Science (DCS) in Enterprise Information System in 2013, Master of Science (MSIT) in Information Technology in 2004, and Bachelor of Science (BSc) in Computer Science in 2000.

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Published

2024-02-12

How to Cite

1.
Dawson JK, Twum F, Acquah JBH, Missah YM. Cryptographic Solutions for Data Security in Cloud Computing: : A Run Time Trend-based Comparison of NCS, ERSA, and EHS. JCSANDM [Internet]. 2024 Feb. 12 [cited 2024 Apr. 28];13(02):265-82. Available from: https://journals.riverpublishers.com/index.php/JCSANDM/article/view/22861

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2024: Vol 13 Iss 2

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