A novel scheme for securing medical data by using hybrid privacy preserving mechanism in health care application

Abstract

Information mining procedures help clinician settle on appropriate choices newlinein medicinal service applications. The advantages of clinical choice emotionally newlinesupportive network incorporate enhancing analysis of sickness exactness as well as newlinediminishing distinguishing proof time. In particular, with huge measures of clinical newlineinformation produced regular, choice tree calculation can be used to uncover newlineimportant information to enhance clinical choice emotionally supportive network. newlineThis information contains insights about healing centers, patients, restorative cases newlineand treatment cost. Along these lines, there is a need to produce an intense newlineapparatus for breaking down and separating essential information from this mind newlineboggling information. In this way the proposed system utilizing Advanced newlineBayesian Belief Network, doctors and patients can without much of a stretch newlinerecognize open medications and discover which procedure for lung disease is newlinebetter and financially savvy. Progressed BBN additionally perceives the symptoms newlineof specific treatment, to settle on suitable choice to diminish the danger and to newlinecreate savvy procedures for treatment. newlineMoreover, our proposed work coordinates both the homomorphic newlineencryption and navie bayes for putting away the information in database safe way. newlineKeeping in mind the end goal to recover the information securely and order the newlinestrange and ordinary information fuzzy based logic is utilized here. newlineThe user dataset can be classified into classes along with some medical newlinefeatures then the categorized data secured by homomorphic algorithm. The secured newlinedataset will be converted to normal and abnormal one based on the disease features newlineby Fuzzy logic. newline