Security Techniques for Remote Healthcare Systems

The Internet of Medical Things (IoMT) has revolutionized healthcare by utilizing
IoT devices and diverse data sources to provide personalized and efficient
care through real-time communication, remote monitoring, and diagnostics. Medical
images, central to IoMT systems, require robust security measures to prevent
unauthorized access and ensure integrity. However, their sensitive nature, complex
networks, and large file sizes increase vulnerability to cyberattacks and unauthorized
modifications, which could lead to improper diagnoses and treatments.
This research introduces several innovative advancements to strengthen IoMT security.
A novel encryption technique is proposed to reduce processing time and
image size while maintaining robust security. A hybrid crypto-system integrates
encryption and watermarking to protect medical images efficiently. A lightweight
watermarking algorithm based on K-means clustering enhances tamper detection
with minimal computational overhead. A blockchain-based watermarking scheme
ensures tamper-proof image transmission without third-party involvement. Furthermore,
a clustering algorithm is designed to preserve data privacy in resourceconstrained
IoMT environments, and a dual watermarking framework provides
comprehensive tamper detection and authentication.
These contributions collectively enhance IoMT security, reliability, and applicability,
supporting the evolution of remote healthcare. The proposed solutions are
validated through simulations and real-world scenarios involving network devices.