Blockchain-Based Cybersecurity in Internet of Medical Things (IoMT)-Based Assistive Systems

Blockchain-Based Cybersecurity in Internet of Medical Things (IoMT)-Based Assistive Systems

Amit Kumar Tyagi (National Institute of Fashion Technology, New Delhi, India), Timothy Thomas George (Vellore Institute of Technology, Chennai, India), and Gulshan Soni (MSEIT, MATS University, India)
DOI: 10.4018/978-1-6684-8938-3.ch002
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Abstract

Today's internet of medical things (IoMT) devices has revolutionized healthcare by enabling the development of assistive systems that enhance patient care and improve healthcare outcomes. However, the increasing connectivity and data exchange in IoMT systems raise issues about cybersecurity and patient data privacy. This chapter explains the application of blockchain-based cybersecurity in IoMT-based assistive systems. Blockchain technology offers a decentralized and immutable ledger that ensures the integrity, security, and transparency of data in IoMT systems. By adding blockchain, cybersecurity challenges in IoMT can be addressed effectively (with providing several benefits, including enhanced data protection, secure identity management, and robust access control mechanisms). Generally, in a blockchain-based cybersecurity framework for IoMT, patient health data is stored in encrypted form on the blockchain, preventing unauthorized access/ tampering. Smart contracts, programmable blockchain protocols, can automate access control and consent management, etc.
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1. Introduction

1.1 Overview of IoMT-Based Assistive Systems

Internet of Medical Things based assistive systems refer to the integration of medical devices, sensors, and healthcare systems with the internet to provide advanced monitoring, diagnostic, and assistance capabilities for individuals in need of medical support (Bai & Liu, 2020). These systems add the power of connectivity and data analysis to enhance healthcare delivery, improve patient outcomes, and enable more personalized and proactive care. Here is an overview of IoMT-based assistive systems and their key components:

  • Medical Devices and Sensors: IoMT systems incorporate various medical devices and sensors to capture and monitor physiological data. These can include wearable devices like fitness trackers, smartwatches, and biosensors that measure parameters such as heart rate, blood pressure, glucose levels, and activity levels. Additionally, home monitoring devices such as blood glucose meters, blood pressure monitors, and spirometers may be connected to the IoMT network.

  • Data Collection and Transmission: The collected data from medical devices and sensors is securely transmitted to a centralized platform or cloud infrastructure through wireless technologies like Bluetooth, Wi-Fi, or cellular networks. This allows healthcare providers to access and analyze the data in real-time, regardless of the location of the patient.

  • Cloud Infrastructure: The cloud infrastructure serves as a centralized repository for storing and processing the collected data. It provides scalability, high availability, and security for the large amount of data generated by IoMT devices. Cloud platforms also enable advanced analytics, machine learning, and artificial intelligence algorithms to derive meaningful information from the data.

  • Data Analytics and Artificial Intelligence: IoMT-based assistive systems add data analytics and AI techniques to interpret the collected data and provide important information. These systems can detect patterns, identify anomalies, and generate predictive models to assist in disease management, early detection of potential health issues, and proactive interventions. AI algorithms can also help in decision support, suggesting appropriate treatment plans or medication adjustments.

  • Remote Monitoring and Telemedicine: IoMT enables remote monitoring of patients, allowing healthcare providers to track important signs and health parameters without the need for in-person visits. Telemedicine applications integrate with IoMT systems, enabling remote consultations between patients and healthcare professionals through video conferencing, messaging platforms, or mobile apps. This enhances access to care, especially for individuals with limited mobility or living in remote areas.

  • Personalized and Adaptive Care: IoMT-based assistive systems can provide personalized care by analyzing an individual's health data and tailoring interventions and treatment plans accordingly. By continuously monitoring a person's health status, these systems can adapt and provide timely alerts or recommendations for lifestyle modifications, medication adherence, and early intervention to prevent adverse health events.

  • Health Data Privacy and Security: As IoMT involves the transmission and storage of sensitive health information, robust security measures are crucial. Data encryption, authentication, and access control mechanisms ensure the privacy and confidentiality of patient data. Compliance with regulatory standards such as HIPAA (Health Insurance Portability and Accountability Act) is essential to protect patient rights and maintain data integrity.

Hence, IoMT-based assistive systems hold immense potential to revolutionize healthcare by improving patient care, reducing healthcare costs, and enabling proactive interventions. However, challenges such as interoperability, data standardization, and ethical issues surrounding data privacy and security need to be addressed to realize the full benefits of these systems.

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