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IMPROVING THE EFFICIENCY OF HEALTH SYSTEM USING MACHINE LEARNING

Abstract

Lately, Remote sensor networks have been broadly utilized in medical care applications, like clinic and home patient observing. Remote clinical sensor networks are more defenseless against listening in, modification, pantomime and replaying assaults than the wired organizations. A great deal of work has been done to get remote clinical sensor organizations. The current arrangements can ensure the patient information during transmission, yet can't stop within assault where the overseer of the patient data set uncovers the touchy patient information. In this paper, proposing a useful way to deal with forestall within assault by utilizing various information workers to store patient information. The principle commitment of this paper is safely appropriating the patient information in different information workers and utilizing the Paillier and ElGamal cryptosystems to perform measurement examination on the patient information without trading off the patients' security. Remote clinical sensor networks surely improve patient's nature of-care without upsetting their solace. Notwithstanding, there exist numerous potential security dangers to the patient touchy physiological information communicated over the public diverts and put away in the back-end frameworks. Average security dangers to medical services applications with WSNs can be summed up as follows. Snoopping is a security danger to the patient information protection. A snoop, having an amazing recipient reception apparatus, might have the option to catch the patient information from the clinical sensors and thusly realizes the patient's ailment. It may even post the patient's ailment on interpersonal organization, which can represent a genuine danger to patient protection. Pantomime is a security danger to the patient information legitimacy. In a home consideration application, an aggressor may mimic a remote depend point while patient information is sending to the distant area.

Author

Ms.S.Kiruba (Assistant Professor), 2 Ms.R.Jenanika , 3 S.Keerthana , 4 B.Devi Priya , 5 R.Logesan
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