Effectiveness of pseudorandom number generators in secret image retrieval fidelity for steganography
Department of Computer Engineering, College of Computing and Informatics, University of Sharjah, U.A.E.
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2024, 12(01), 289–297.
Article DOI: 10.30574/wjaets.2024.12.1.0238
Publication history:
Received on 04 May 2024; revised on 09 June 2024; accepted on 12 June 2024
Abstract:
Steganography, an ancient technique for concealing information within seemingly benign data, has resurfaced in the digital age, finding widespread application across a variety of industries. However, its use confronts major hurdles, notably with image files that are susceptible to network transmission distortions and assaults. Pseudorandom Number Generators (PRNGs) emerge as critical safeguards in this setting, increasing the unpredictability of embedded data and thwarting malevolent manipulations. This study evaluates the usefulness of various PRNGs in reinforcing LSB steganography to secure the integrity and retrievability of concealed data after transmission. Six PRNGs, including LCG, PCG, and XORshift, were evaluated, and the results show that they are successful at preventing both distortions and attacks. Notably, non-randomized images of type PNG are resistant to transmission distortions but struggle with secret image retrieval post-attack. This research advances steganographic methodologies, offering insights into fortifying digital communication amidst real-world challenges.
Keywords:
Pseudorandom Number Generator; PRNG; Secret Image; Retrieval Fidelity; Steganography; Information Security
Full text article in PDF:
Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0