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Medical Secure Systems (MSSs) are characterized by integrating computation and physical processes. The theories and applications of MSSs Face the enormous challenges. The aim of this work is to provide a better understanding of this emerging multidisciplinary methodology. In this work we focused on the MSS in medical applications, which is known as Medical Secure Systems (MSS). In MSS, multiple data can be transmitting to the private or public cloud for storage and processing. Over these data, machine learning algorithms can be applied to process that data, which will be further useful to take some decisions for healthcare professional. This data can be sensitive and is publically available and provided to third party storage space, so that the challenging issue of security is arises. To provide the security, in this paper we applied cryptographic technique such as AES to encrypt the data before store on cloud servers. After this, to enhance the further security, we will use the concept of digital envelope. In this concept, data encryption AES key is again encrypted by using ECC encryption key. Again to reduce the key management overhead, system makes use of Key Distribution Center (KDC), which can generate and manage the keys for all users. Finally experimental results prove that, this MSS system is more secure than previous one and it is also reduce the key management overhead.
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