A Novel Hybrid Algorithm for Securing Data Transfer with machine Learning Disease Prediction
Varalakshmi, Vasantha Raja . S.S, Vijaya Narayanan . A, Saravanan .S
Data Security, Encryption, Hashing, Hackable, Token, Diabetes
Data security refers to the process of protecting data from unauthorized access and data corruption throughout its life cycle. Data security includes data encryption, hashing, tokenization, and key management practices that protect data across all applications and platforms. The security system used nowadays uses data encryption software to effectively enhance data security by using an algorithm (called a cipher) and an encryption key to turn normal text into encrypted cipher text. To an unauthorized person, the cipher data will be unreadable. That data can then be decrypted only by a user with an authorized key. Whereas with the improving data insecurity nowadays leads to loss of confidential data as the key is easily hack able because of a single algorithm usage. Diabetes-related complications include damage to large and small blood vessels, which can lead to heart attack and stroke, and problems with the kidneys, eyes, feet and nerves. The risk of most diabetes-related complications can be reduced if diagnosed early. To overcome this problem this project presents a medical application that accepts and analyses a patient’s medical data to give a diagnosis to check if he/she is diabetic with an efficient data security system where two security algorithms will be merged to secure the patient’s medical data stored and accessed in cloud. In addition, the emerging block chain technologies with the wireless data transfer system, which makes easy the interaction between the data and cloud. The medical data is analyzed and the result is stored securely in a cloud database such as mongoDB as an highly secure encrypted key. The result is received from the database and decrypted in the frontend to view the test results. Thus, this project presents an effective end to end security for medicalapplications.
Article Details
Unique Paper ID: 153333

Publication Volume & Issue: Volume 8, Issue 6

Page(s): 565 - 573
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