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Cloud Computing is a boon to the field of information and technology. The two major elements of client worries are Data security and Privacy Protection. Data may be revised and improved when client stores the information in the cloud so there might be danger of data loss. Therefore client information is moved to the data hub which cannot be controlled by the clients. Hence high safety efforts are required to secure data inside the cloud. Here data is divided into fragments and they are converted into encrypted file. This encrypted file is issued to arbitrarily chosen cloud service providers by the cloud data owners. Even after the successful attack, attackers do not get the meaning full information. If cloud data clients access to get any document that relating to encrypted file is regenerated from the fragments and clients must download it. When the applicant coordinates the strategy with the original details, then only file can be decoded. Therefore it demonstrates that prospective strategy improves the data integrity and confidentiality.

In the recent years, the most difficult task in medical sciences is to foresee a heart disease. This gives birth to the necessity for the decision support system developed to predict the heart disease of a patient. In case of disease prevention and disease treatment the decision-making marks a remarking step. The increasing demand of efficient healthcare organizations are encroached with the challenges to provide cost-efficient and superior quality patient care. To cope up with the huge databases of health care information systems to discover the relevant knowledge of decision making, Knowledge Data Discovery, is carried out through data mining. The procedure involved in the efficient use of the healthcare data through extraction and pattern discovery is referred to as data mining. It also acts as a study tool to learn the veiled relationships in heart disease healthcare data. These methods reveal various consistent primary recognition systems from clinical and diagnosed data. These methods require less time and produce more accurate results. This paper contains comparisons and results of different evaluation methods. Focusing greatly on developing a prototype that reveals the veiled knowledge of heart disease from past records with the help of a hybrid genetic algorithm. Thus, helping the medical practitioners to take up the right decision on right time providing appropriate treatments.