Severity Based Light-Weight Encryption Model for Secure Medical Information System

As the amount of medical images transmitted over networks and kept on online servers continues to rise, need protect those digitally is becoming increasingly important. However, due massive amounts multimedia pictures being exchanged, low computational complexity techniques have been developed. Most commonly used algorithms offer very little security require a great deal communication, all which add high processing costs associated with using them. First, deep learning classifier classify records according degree concealment they require. Medical that aren’t needed can be saved by this method, cuts down costs. Encryption one most effective methods for protecting after step. Confusion dispersion are two fundamental encryption processes. A new algorithm sensitive data developed in study. Picture splitting image blocks now Zigzag patterns, rotation blocks, random permutation scrambling blocks. After that, research suggests Region Interest (ROI) technique based selective picture encryption. For first step, we use an active contour segmentation separate ROI from Background (ROB). Permutation diffusion then carried out Hilbert curve Skew Tent map. Once encrypted, combined create encrypted images. The investigational analysis test competence projected ideal existing techniques.