Self-diagnosis platform via IOT-based privacy preserving medical data

Abstract

Healthcare is one of the application domains that use IoT technology, where sensors and IoT-enabled medical devices transmit data to healthcare specialists without the need for human intervention. The health records of previous patients are both very confidential and crucial to the identification of the disease for current patients. Therefore, it is important to fully utilize the records of previous patients without disclosing their personal data. This paper proposes an innovative Self Diagnosis Platform (SDP) that securely retrieves patients' records from past records without disclosing either the privacy of the patient or the record database. Initially, the patient device receives data from the sensors placed in the patient's body, which is then encrypted by using Edwards' Digital Signature Algorithm. The encrypted data is then sent to the Secure Disease Archive (SDA), which contains past records. Based on the patient's data, similar records will be retrieved from the database using the SDP. The suggested framework is compared with traditional methods in terms of encryption time, execution time, and end-to-end delay. Experimental results indicate that the suggested SDP technique achieves a better execution time of 30.63%, 27.48%, 22.07%, and 9.23% than LDQN, SE-AC, PMDA, and EPPDA methods. This system is more effectiveand secure for real-time applications.

Keywords

• Internet of things
• Self-diagnosis platform
• Security
• Edward's digital signature algorithm
• Encryption
• Decryption