Cloud-based Reversible Dynamic Secure Steganography Model for embedding pathological report in medical images

Abstract

ABSTRACT Over past decades, several research works have been published in the direction of hiding confidential data that includes only the patients personal details in medical images. The medical images and respective pathological reports are stored separately in the storage device. Storing medical images and pathological reports separately occupy more storage compared to storing pathological reports Stego in medical images. This research identified pixel space available in the medical image for storing other relevant secret information. In this technique, a new algorithm is proposed for generating secret keys. The secret keys are utilized to segment the medical image into five regions: (i) one Region of Interest (ROI) sub-image and (ii) four non-Region of Interest sub-images. From the four non-Region of Interest sub-images, a particular non-ROI region sub-image is randomly selected from the secret key matrix. The pathological report is embedded into the preprocessed selected non-ROI region sub-image of the medical image and generated the Stego medical image. The Stego medical image and secret key are communicated using various network communication applications to the user for deStego the original X-ray image and pathological report at the user end. The research work confirmed the quality of the medical image using MSE and PSNR values.