Implementation of a steganography system based on hybrid square quaternion moment compression in IoMT

Mohamed Amine Tahiri, Ahmed Bencherqui, Hicham Karmouni, Hicham Amakdouf, Seyedali Mirjalili, Saad Motahhir, Mohamed Abouhawwash, S. S. Askar, Mhamed Sayyouri, Hassan Qjidaa

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Internet of Medical Things (IoMT) systems generate medical data transmissions between patients, medical experts, and medical centers over public networks, which require high levels of security to protect the content of medical images and the personal information they contain. In this paper, we propose a new stego image encryption scheme based on a new secret image compression method, wavelet transformation, QR decomposition of the cover image, and a new chaotic map. The secret image is compressed by the Hahn-Krawtchouk hybrid quaternion square moments (HK-HQSM), which are optimized by a new hybrid metaheuristic algorithm based on the Salp Swarm Algorithm (SSA) and the Arithmetic Optimization Algorithm (AOA). To increase the security level when transmitting the proposed stego images over public networks, we introduce a new chaotic map based on the 2D fractional Henon map to encrypt the stego image. To demonstrate the effectiveness of the proposed steganography scheme for IoMT, we implemented this scheme on a low-cost Raspberry Pi 4 hardware board. The results of the performed numerical experiments show that our method is secure and provides exceptional robustness against common standard image processing attacks (steganalysis attacks). The results also demonstrate that our strategy is able to work efficiently and quickly when implemented on a Raspberry Pi board.

Original languageEnglish
Article number101604
JournalJournal of King Saud University - Computer and Information Sciences
Issue number7
Publication statusPublished - Jul 2023


  • Hybrid square moments
  • Image steganography
  • Index Terms
  • Internet of Medical Things
  • Optimization algorithm
  • Raspberry Pi


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