A Novel SPN based Multiple RGB Images Security over the Residue Classes of Quaternion Integers H[K]_δ
In this paper, we propose a Substitution and Permutation Network (SPN)-based encryption scheme for secure multiple RGB images over the residue classes of quaternion integers H[K]_δ. In this context, the new construction of n×n substitution boxes (S-boxes) using quaternion integers is proposed in order to enhance cryptographic strength. The traditional approaches for S-boxes are mostly based on Gaussian, Eisenstein, and elliptic curves, but quaternion integers are a four-dimensional algebra that is somewhat different mathematically, and these provide additional resistance in terms of cryptographic attacks. The strong security attributes of the designed S-boxes. As for multiple RGB image encryption, in order to achieve both confusion and diffusion, the proposed method employs the SPN framework and quaternion integer-based S-boxes. Structured SPN framework based on substitution, permutation, and XOR operations used by the encryption algorithm. It is shown that the encryption method proposed greatly increases the resistance against statistical, differential, and cryptanalytic attacks. The quaternion integer-based encryption framework is used to convey the confidentiality and integrity of multiple RGB images, which promises to be a good solution for secure multimedia applications. The results confirm that quaternion integer algebra can constitute a useful basis for constructing resilient cryptographic primitives for the modern digital security challenges
Authors
- Muhammad Sajjad (ORCID: https://orcid.org/0000-0003-0006-1156)
- Nawaf A. Alqwaifly (ORCID: https://orcid.org/0009-0004-2455-0936)
Institutions
- Qassim University (SA)
- National University of Technology (PK)
Publication Details
- Journal
- European Journal of Pure and Applied Mathematics
- Published
- 2025-05-01
- DOI
- https://doi.org/10.29020/nybg.ejpam.v18i2.6228
- Citations
- 4
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 3.37
Funders
- Qassim University