Design an Iot Enabled Healthcare System for Improving the Performance of Security and Authentication in Cloud Computing

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Published: Oct 19, 2022
Keywords:
Random Forest, Identity-based Encryption, Patient Health Records, Whale optimization, Attacks, Authentication, and Security.

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Shivakumaraswamy GM
Department of Electrical and Electronics Engineering, Bapuji Institute of Engineering and Technology, Davangere 577005, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India Department of Electronics and Communication Engineering, Institute of Engineering and Technology, Srinivas University, Mukka, Mangaluru 574146, Karnataka, India
Dr. Rajanna GS
Department of Electronics and Communication Engineering , Institute of Engineering and Technology, Srinivas University, Mukka, Mangaluru 574146, Karnataka, India
Dr. Ashoka K
Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere 577005, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India

Abstract

Attacks, illegal access, and other variables have made a data analytics-based healthcare
system more exposed in recent years. It is simpler for hackers to get access to the server and
steal data because of the initial state of the system's components. An innovative Identitybased
Encryption Random Forest model with Whale Optimization (IBERF-WO) is used in
this research design to encrypt data and protect patient information from threats and
unauthorized access. Additionally developed models improve patient-sensitive data by
providing better security and authentication. Whale fitness is maintained in the planned
model for continuously monitor attacks or any unauthorized access to the network. To train
the system, more than 200 patient datasets are used, and the developed framework is
implemented in the Python tool. Finally, the healthcare records of diverse patients are
effectively encrypted and stored in the cloud. Attacks are then made against the constructed
model to assess its reliability and efficiency. In the conclusion, the performance results of the
developed framework are evaluated in terms of energy consumption, execution time,
encryption time, latency, accuracy, and decryption time in comparison to other conventional
methods.

Article Details

Issue
Vol 21, No 1 (2022)
Section
Articles