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The recent advancement in computing technologies and resulting vision basedapplications have gives rise to a novel practice called telemedicine thatrequires patient diagnosis images or allied information to recommend or evenperform diagnosis practices being located remotely. However, to ensure accurateand optimal telemedicine there is the requirement of seamless or flawlessbiomedical information about patient. On the contrary, medical data transmittedover insecure channel often remains prone to get manipulated or corrupted byattackers. The existing cryptosystems alone are not sufficient to deal withthese issues and hence in this paper a highly robust reversible imagesteganography model has been developed for secret information hiding. Unliketraditional wavelet transform techniques, we incorporated Discrete RippletTransformation (DRT) technique for message embedding in the medical coverimages. In addition, to assure seamless communication over insecure channel, adual cryptosystem model containing proposed steganography scheme and RSAcryptosystem has been developed. One of the key novelties of the proposedresearch work is the use of adaptive genetic algorithm (AGA) for optimal pixeladjustment process (OPAP) that enriches data hiding capacity as well asimperceptibility features. The performance assessment reveals that the proposedsteganography model outperforms other wavelet transformation based approachesin terms of high PSNR, embedding capacity, imperceptibility etc.

An Evolutionary Computing Enriched RS Attack Resilient Medical Image Steganography Model for Telemedicine Applications