Secure Euclidean random distribution for patients’ magnetic resonance imaging privacy protection
Ali Jaber Tayh Albderi,
Lamjed Ben Said
Abstract:Patients’ information and images transfer among medical institutes represent a major tool for delivering better healthcare services. However, privacy and security for healthcare information are big challenges in telemedicine. Evidently, even a small change in patients’ information might lead to wrong diagnosis. This paper suggests a new model for hiding patient information inside magnetic resonance imaging (MRI) cover image based on Euclidean distribution. Both least signification bit (LSB) and most significat… Show more
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