Please use this identifier to cite or link to this item: https://hdl.handle.net/10953/2322
Title: Robust, Reversible Medical Image Watermarking for Transmission of Medical Images over Cloud in Smart IoT Healthcare
Authors: Devi, K.J.
KrisHna, M.V.J.
Singh, P.
Santamaria, J.
Barakaniya, P.
Abstract: There has been a significant advancements in the field of e-healthcare. E-healthcare applications are changing and adapting to improve smart healthcare domain employing IoT devices, making working in the healthcare domain more convenient. For diagnosis and treatment, medical images are transferred through cloud from radiology center to smart healthcare centres. Among the contentions that causes problems in medical image transmission is the integrity and confidentiality of medical images on the smart healthcare platform. Another major challenge with ensuring protection for electronic patient health records (EHR) in the cloud infrastructure is the confidentiality of patient records. Hence medical image watermarking helps to maintain their authenticity, confidentiality and integrity. Here proposing a reversible medical image watermarking scheme in the spatial domain that embedded EHR in the medical cover image at the sender and the same watermark is retrieved and original image is restored at the receiver end. The embedding is done using the quadratic difference expansion and the data encryption is done using the magic polybius music square to ensure high embedding capacity and security. From the obtained experimental results satisfied all watermarking characteristics.
Keywords: Ramdon Key
Image watermarking
Internet of Medical Things
Smart Healthcare
Issue Date: 22-Sep-2022
Publisher: Springer
ISBN: 978-3-031-18033-0
Citation: Devi, K.J., Krishna, M.V.J., Singh, P., Santamaría, J., Bakaraniya, P. (2023). Robust, Reversible Medical Image Watermarking for Transmission of Medical Images over Cloud in Smart IoT Healthcare. In: Thakkar, H.K., Dehury, C.K., Sahoo, P.K., Veeravalli, B. (eds) Predictive Analytics in Cloud, Fog, and Edge Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-18034-7_2
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