Baagyere, E.Y., Agbedemnab, P.A., Qin, Z., Daabo, M.I. and Qin, Z.G. (2020) A Multi-Layered Data Encryption and Decryption Scheme Based on Genetic Algorithm and Residual Numbers. IEEE Access, 8, 100438-100447.
https://doi.org/10.1109/ACCESS.2020.2997838

has been cited by the following article:

• TITLE: A New Image Watermarking Scheme Using Genetic Algorithm and Residual Numbers with Discrete Wavelet Transform

  AUTHORS: Peter Awonnatemi Agbedemnab, Mohammed Akolgo, Moses Apambila Agebure

  KEYWORDS: Discrete Wavelet Transform (DWT), Digital Watermarking, Encryption, Genetic Algorithm (GA), Residue Number System (RNS), GARN

  JOURNAL NAME: Journal of Information Security, Vol.14 No.4, October 18, 2023

  ABSTRACT: Transmission of data over the internet has become a critical issue as a result of the advancement in technology, since it is possible for pirates to steal the intellectual property of content owners. This paper presents a new digital watermarking scheme that combines some operators of the Genetic Algorithm (GA) and the Residue Number (RN) System (RNS) to perform encryption on an image, which is embedded into a cover image for the purposes of watermarking. Thus, an image watermarking scheme uses an encrypted image. The secret image is embedded in decomposed frames of the cover image achieved by applying a three-level Discrete Wavelet Transform (DWT). This is to ensure that the secret information is not exposed even when there is a successful attack on the cover information. Content creators can prove ownership of the multimedia content by unveiling the secret information in a court of law. The proposed scheme was tested with sample data using MATLAB2022 and the results of the simulation show a great deal of imperceptibility and robustness as compared to similar existing schemes.