A Critical Study on Internet of Medical Things for Secure WBAN

A Critical Study on Internet of Medical Things for Secure WBAN

Saima Sultana (Hamdard University, Pakistan), Shamim Akhtar (Majmaah University, Saudi Arabia), Sadia Nazim (Hamdard University, Pakistan), Pardeep Kumar (Quaid-e-Awam University of Engineering, Science and Technology, Pakistan), Manzoor Ahmed Hashmani (University Technology PETRONAS, Malaysia) and Syed Sajjad Hussain Rizvi (Hamdard University, Pakistan)
DOI: 10.4018/978-1-7998-2803-7.ch009
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Abstract

During the recent decade, wireless body area network (WBAN) was developed and prioritized. This gives reliability, energy efficiency, and guaranteed results. Moreover, internet of medical things (IoMT) also enhances the significance of WBAN networks. To achieve high throughput, performance, and efficiency, WBAN deserves a new protocol definition as compared to general wireless sensor network along with a more enhanced framework. The standard 802.15.6 with PHY and MAC layers follow the standardization of WBAN. The wireless nature of the network and various varieties of sensors in the presence of IoMT made it possible to develop new, effective, innovative, and demand-driven solutions for health improvement and quality of service. In the recent literature, the researchers have proposed an IoMT-based secure framework for WBAN. In this chapter, an in-depth and comprehensive depiction of the security issues of IoMT-based framework of the wireless network is highlighted that incorporates security measures in different levels of the WBAN network.
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Introduction

he rising population in the world hits the paradigm of discovered technology to drive solutions to the problematic era. At the edge of decay, various automated phases of human life interact concisely with technological enhancements to seek worth, pleasure, and comfortability in an effective manner. According to a survey total population in Pakistan is about 207,774,000, as of July 2019, based on the latest United Nations estimation. Pakistan's population equals to 2.65% of the total world population. It declares a noticeable and markable figure for elderly people included. Figure 1 shows the graphical comparison between ages and available population in percentage while Table 1 shows further specification. To survive a healthy life, elderly persons endure one of the major issues as high healthcare costs. This is very crucial to take care of either an elderly person or a patient who is not fit physically may have some healthcare issues(Singh & Singh, 2016). With some dominant aspects, his caregiving lies in cost, security, comfort and reliability issues. In many cases like an injury or after a severe accident, it is mandatory for the patient to care deeply and sensitively. To stay at the hospital sometime gives anxiety and frustration. Cost, privacy and limitation on patients are other major concerns (Hayajneh, Almashaqbeh, Ullah, & Vasilakos, 2014) (Van Daele, Moerman, & Demeester, 2014).

The available proposed solution could be the use of technology as some tiny, cheap and less weight intelligent sensors are invented. Those sensors could be worn up or embedded in the side or around the body (Cavallari, Martelli, Rosini, Buratti, & Verdone, 2014). These sensors send their data that is a vital sign to an attached server, either wired or wireless. The wired one is much complex and costly for deployment and maintenance too. The wireless system is much cost-effective and easy to use. In lieu to achieve wireless system through sensors on or inside the body wireless sensor network works. Specifically to get entire achievements a new network comes into being, named Wireless Body Area Network (WBAN) (Van Daele et al., 2014). For transmission of vitals bring together from the patient to the medical expert, present in a remote location. An efficient, secure, reliable, up to date framework is required. So in this research paper, an IoMT based secure framework for WBAN is proposed.

Figure 1.

Age paradigm

978-1-7998-2803-7.ch009.f01
Table 1.
Population Criteria
Age% AgeMaleFemale
0-14 years31.36%33,005,62331,265,463
15-24 years21.14%22,337,89720,980,455
25-54 years37.45%39,864,41736,907,683
55-64 years5.57%5,739,8175,669,495
65+4.48%4,261,9174,910,0945

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