Description

Health care monitoring is the one of popular streaming data application. Here we proposed to a novel methodology for mining frequent item sets through patient disease records. Here address the problem of multiple patient records and disease details are security based stored in cloud server through Elliptic curve cryptography. Elliptic-curve cryptography (ECC) is an approach to public-key cryptography based on the algebraic structure of elliptic curves over finite fields. ECC requires smaller keys compared to non-ECC cryptography (based on plain Galois fields) to provide equivalent security. Identifying the participants at risk isimportant for early warning and preventive intervention. The fundamental challenge of learning a classification model for risk predictionlies in the unlabeled data that constitutes the majority of the collected dataset. Particularly, the unlabeled data describes theparticipants in health examinations whose health conditions can vary greatly from healthy to very-ill. Here different types of diseases based analysing and stored into database and find the high risk patient disease informations are stored in cloud server.