Hybrid optimization with cryptography encryption for medical image security in Internet of Things


The development of the Internet of Things (IoT) is predicted to change the healthcare industry and might lead to the rise of the Internet of Medical Things. The IoT revolution is surpassing the present-day human services with promising mechanical, financial, and social prospects. This paper investigated the security of medical images in IoT by utilizing an innovative cryptographic model with optimization strategies. For the most part, the patient data are stored as a cloud server in the hospital due to which the security is vital. So another framework is required for the secure transmission and effective storage of medical images interleaved with patient information. For increasing the security level of encryption and decryption process, the optimal key will be chosen using hybrid swarm optimization, i.e., grasshopper optimization and particle swarm optimization in elliptic curve cryptography. In view of this method, the medical images are secured in IoT framework. From this execution, the results are compared and contrasted, whereas a diverse encryption algorithm with its optimization methods from the literature is identified with the most extreme peak signal-to-noise ratio values, i.e., 59.45 dB and structural similarity index as 1.

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Correspondence to Mohamed Elhoseny.

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Elhoseny, M., Shankar, K., Lakshmanaprabu, S.K. et al. Hybrid optimization with cryptography encryption for medical image security in Internet of Things. Neural Comput & Applic 32, 10979–10993 (2020). https://doi.org/10.1007/s00521-018-3801-x

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  • IoT
  • Medical images
  • Cloud
  • Encryption
  • Decryption
  • Optimization
  • PSO
  • Grasshopper optimization
  • ECC