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Secure Medical Data Transmission Model for IoT-Based Healthcare Systems

Authors :
Shihab A. Shawkat
Osama Abu-Elnasr
Gustavo Ramirez-Gonzalez
N. Arunkumar
Mohamed Elhoseny
Ahmed Farouk
Source :
IEEE Access, Vol 6, Pp 20596-20608 (2018)
Publication Year :
2018
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2018.

Abstract

Due to the significant advancement of the Internet of Things (IoT) in the healthcare sector, the security, and the integrity of the medical data became big challenges for healthcare services applications. This paper proposes a hybrid security model for securing the diagnostic text data in medical images. The proposed model is developed through integrating either 2-D discrete wavelet transform 1 level (2D-DWT-1L) or 2-D discrete wavelet transform 2 level (2D-DWT-2L) steganography technique with a proposed hybrid encryption scheme. The proposed hybrid encryption schema is built using a combination of Advanced Encryption Standard, and Rivest, Shamir, and Adleman algorithms. The proposed model starts by encrypting the secret data; then it hides the result in a cover image using 2D-DWT-1L or 2D-DWT-2L. Both color and gray-scale images are used as cover images to conceal different text sizes. The performance of the proposed system was evaluated based on six statistical parameters; the peak signal-to-noise ratio (PSNR), mean square error (MSE), bit error rate (BER), structural similarity (SSIM), structural content (SC), and correlation. The PSNR values were relatively varied from 50.59 to 57.44 in case of color images and from 50.52 to 56.09 with the gray scale images. The MSE values varied from 0.12 to 0.57 for the color images and from 0.14 to 0.57 for the gray scale images. The BER values were zero for both images, while SSIM, SC, and correlation values were ones for both images. Compared with the state-of-the-art methods, the proposed model proved its ability to hide the confidential patient's data into a transmitted cover image with high imperceptibility, capacity, and minimal deterioration in the received stego-image.

Details

ISSN :
21693536
Volume :
6
Database :
OpenAIRE
Journal :
IEEE Access
Accession number :
edsair.doi.dedup.....777be803b9a4e59357d33f517aac2b12
Full Text :
https://doi.org/10.1109/access.2018.2817615