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Edge-Enabled Hybrid Encryption Framework for Secure Health Information Exchange in IoT-Based Smart Healthcare

Norjihan Abdul Ghani1,2, Bintang Annisa Bagustari1, Muneer Ahmad3

  • 1Department of Information Systems, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur 50603, Malaysia.

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Summary

This study introduces a secure hybrid encryption framework for Internet of Things (IoT) healthcare systems. The edge-enabled approach enhances data security and privacy during health information exchange (HIE).

Keywords:
IoT-based smart healthcareedge-enabled encryptionhealth information exchangehybrid algorithms

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Health Informatics

Background:

  • The Internet of Things (IoT) and edge computing are revolutionizing healthcare, enabling real-time patient data processing.
  • However, the distributed nature of these systems creates significant security and privacy vulnerabilities during health information exchange (HIE).

Purpose of the Study:

  • To propose and evaluate an edge-enabled hybrid encryption framework for secure HIE in IoT healthcare systems.
  • To systematically compare different hybrid encryption configurations for efficiency and security.

Main Methods:

  • Developed an edge-enabled hybrid encryption framework combining Elliptic Curve Cryptography (ECC), HMAC-SHA256, and Advanced Encryption Standard (AES).
  • Executed encryption and verification at the network edge to minimize latency and cloud dependency.
  • Evaluated CPU usage, memory consumption, and scalability across various data volumes.

Main Results:

  • The ECC + HMAC-SHA256 + AES configuration demonstrated high encryption efficiency and robust security against attacks.
  • The framework achieved lightweight processing, suitable for resource-constrained edge devices.
  • The proposed model showed scalability for varying data volumes in edge-based HIE.

Conclusions:

  • The edge-enabled hybrid encryption framework offers a scalable and secure solution for protecting sensitive health data in IoT healthcare.
  • This approach effectively addresses the security and privacy risks associated with HIE in next-generation smart healthcare systems.