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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Dalia H. Elkamchouchi
Princess Nourah bint Abdulrahman University

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A deep learning signed medical image based on cryptographic techniques Dalia H. Elkamchouchi; Abeer D. Algarni; Rania M. Ghoniem; Heba G. Mohamed
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp481-495

Abstract

Innovative medical multimedia communications technology requirements have enhanced safety principles, allowing significant advancement in security standards. In hospitals and imaging centers, massive amounts of medical images have been created. To successfully access the medical databases and utilize those rich resources in assisting diagnosis and research, image processing enabled communication solutions are necessary. Our article presents a rigorous verified model by employing deep learning to enhance the cryptographic performance of biomedical images using hybrid chaotic Lorentz map diffusion and de-oxyribonucleic acid (DNA) confusion stages. It consists of two encryption/decryption techniques, the initial signal is verified using digital signature and two unique non-consecutive stages of chaotic diffusion with a single DNA scrambling stage in between. The encoded secret bit stream is generated and used to encrypt or decode the original signal in the diffusion manner to disintegrate the redundancy in the plain image statistics, utilizing hybrid chaotic system. Using DNA confusion step to make the relationship between the original signal and the utilized key more ambiguous. These stages make the proposed image cryptosystem more resistant to known/ chosen plaintext assaults. The performance of the suggested technique will be assessed to the most similar techniques reported in the literature for comparative purposes.
Co-Authors Abeer D. Algarni Heba G. Mohamed Rania M. Ghoniem