IOT Adoption in Healthcare: Security Concerns and Fog Computing Solutions

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This literature review discusses the adoption of IOT in healthcare, its benefits and challenges, and the security concerns associated with it. It also explores the potential of fog computing as a solution to these concerns. The review highlights the need for enhanced security measures to protect patients' personal and health data. The paper concludes that fog computing is a promising solution to the security concerns associated with IOT in healthcare, but further research is needed to fully implement it.

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Literature review:
This section of the paper will discuss and compare different perspectives of several
authors who published their literature in the context of IOT adoption in healthcare. Some
literatures provides useful information which can assist to understand the adoption of IOT in
healthcare and issues around the adoption (Laplante & Laplante, 2016). In the healthcare sector,
IOT has been developed in multiple key areas and some of the applications likewise remote
monitoring and smart sensors are providing optimal value. Even though, the development in the
health care center is rapidly involving, some critical issues is also occurring while development
process (Zhou & Piramuthu, 2018). Today’s technologies provide first transmission of data but
the security concerns are still cannot be ignored. Many literatures provides their explanation
about certain security measures which have massive impact on the healthcare.
IOT based healthcare system:
Advanced IOT application development and widespread adoption of such devices, have
generate multiple ways to improve healthcare system with numerous advantages as accessibility
and cost effective. The adoption of IOT in healthcare system have alter many typical operation
by enabling multiple functionality with better efficiency. Nowadays, IOT applications are
enabling remote monitoring and personalization and experts believe that it would provide more
optimal value in near future (Gope & Hwang, 2016). An increasing number of smart medical
devices and sensors used in IoT-driven healthcare vision implies the fast generation of huge
amounts of diverse data. In order to successfully deal with increasing amounts of excessive
diversity of information and high speed of data generation and processing it is required to deal with
security and technical concerns. The IOT applications are showing promising results since it
enables self-managing disease and enables remote care and assistance through associated
networked monitoring equipment. However, some critical security issues may appear in the
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healthcare. Most of the healthcare center, stores the patients crucial data into their own database.
These dataset contains valuable information associated with the patients personal and health
history (Bhatt, Dey & Ashour, 2017). As these technologies are engaging with the healthcare
sectors, this devices are storing huge amount of data in them. For instance, smart wear devices
generate health report of the user and also stores this data in them or transfer to cloud. This data
can be easily compromised as not mush of security measures are implemented in those
technologies. This type of issues are hindering the rapid development of the IOT in health care
sector (Laplante & Laplante, 2016). However, there are many research in active state to
implement of an additional layer between cloud and those devices for faster computing and
connectivity. This type of layer are generally refers as fog computing and offer multiple potential
as well. The fog computing is one of the hottest topic in the IOT development as it can provide
enhance security with time sensitivity (Lee & Lee, 2016). However, fog infrastructure can be
utilized up to the full potential until the healthcare infrastructure overcome the issues for its
implementation.
Fog computing:
Multiple author identified Fog computing as a solution of the security and privacy
concerns associated with the IOT development in the healthcare sectors. They also proposed
some simple computing layer in an IOT system. This information are presented as key area in
this section. Fog computing is an innovative trend in computing established by cisco that
spreads the cloud computing archetype at the edge of the network as processing data around data
source. Fog computing also enable Knowledge generation and data analytics features which
compressed the data volume, need to transfer to cloud (Laplante & Laplante, 2016). Generally, in
cloud computing applications and information are processed in the cloud which is very time
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consuming for vast amount of data. As a solution, fog computing placed on the edge of a
network take considerably less time to process the similar tasks. However. Fog computing
cannot work on his own as it cannot replace the cloud computing. It just a solution of cloud
computing limitation (Moosavi et al., 2016). According to the Elhoseny, fog computing is the
most appropriate application compared with other solutions especially for Large-scale distributed
control systems, mobile applications such as smart connected rail or connected vehicle.
Geographically distributed sensor/actuator networks - applications in which thousands or
millions of things across an enormous geographic area are producing data and applications that
involve with very low and predictable expectancy like various emergency response applications
and health-monitoring (Elhoseny et al., 2018). The smart devices and sensors utilized in the
healthcare industry for monitoring the patient’s health status have limited amount of storage
capability and computation. This devices also generates vast amount of data which needs to be
secured from third parties (Bhatt, Dey & Ashour, 2017).
In IoT-powered healthcare applications, event response and real-time processing are vital.
Fog computing enables real-time and online analytic even when connectivity is poor or lost with
the Cloud, and implies less congestion and faster real time interaction and optimizations for IoT
devices what makes it perfect for utilization in IoT-based healthcare systems (Catarinucci et al.,
2015). Author proposed a prototype of the Iot based healthcare system with proper encryption to
the fog node. Generally, the health related data such as patients’ heart rate, blood pressure,
weight and body temperature are directly send to the cloud from the smart devices or sensors as
these type of technologies does not contains sufficient amount of data storage and power source
because of the slim design. Between the smart devices and the cloud there is no security
measures (Da et al., 2014). Fog nodes can be implemented between the devices and cloud to

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enable encryption and security. The data generated by those devices are first sent to the fog sever
for processing the data. This layer is responsible for adding encryption and other security
measurement and then sent to the cloud. This approach is appreciated by many experts as it
provides confidentiality, data integrity, accountability, availability and access control (Laplante
& Laplante, 2016). However, fog computing just an extension of the cloud computing and other
security and privacy concerns will remain the same.
Annotated bibliography:
Moosavi, S. R., Gia, T. N., Rahmani, A. M., Nigussie, E., Virtanen, S., Isoaho, J., &
Tenhunen, H. (2015). SEA: a secure and efficient authentication and authorization
architecture for IoT-based healthcare using smart gateways. Procedia Computer
Science, 52, 452-459.
This paper provides an authorized and authenticated architecture for IOT based
healthcare. The author identified the significance of the privacy and security on the IOT
development in the healthcare sector. The authors provides broad description of SEA and
gateways for enhance the security measures on IOT devices. In the existing architecture and
authorization and authentication of a remote end-user is done by disseminated smart e-health
gateways to unburden the medical sensors from accomplishment these tasks. The offered
architecture depend on the certificate-based DTLS as it is the main ip security solution. (Moosavi
et al., 2015). They also proposed a SEA architecture based on the sensor nodes and the smart
gateways to enable security measures. Their offered architecture is more protected than a state-
of-the-art central delegation-based architecture. This papers also provides a clear understanding
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of the IOT based medical applications. However, they were unable to provide any security
measures for their proposed system (CodeBlue).
Gope, P., & Hwang, T. (2016). BSN-Care: A secure IoT-based modern healthcare system
using body sensor network. IEEE Sensors Journal, 16(5), 1368-1376.
The author of this paper provides a broad description of the secure IOT based modern
healthcare system while utilizing a body sensor network. IOT applications such as advanced
devices and sensors are getting popular as they provide remote monitoring and personalization.
They also illustrate various application of IOT and the development issues associated around
different medical area. They also highlighted the key areas where healthcare sectors can face
challenges due to the poor security and privacy measure(Gope & Hwang, 2016). According to
the author, the rapid propagation of communication and information technologies is allowing
advanced tools and healthcare solutions that display promises in addressing the aforesaid issues.
Islam, S. R., Kwak, D., Kabir, M. H., Hossain, M., & Kwak, K. S. (2015). The internet of
things for health care: a comprehensive survey. IEEE Access, 3, 678-708.
This paper analyzes different IoT privacy and security features, including attack
taxonomies, threat models, security requirements, and from the health care viewpoint. The IoT
offers suitable results for a wide range of applications such as health care, industrial control,
retails, logistics, emergency services, security, structural health, waste management, traffic
congestion and smart cities. They also developed an intelligent collaborative security model to
minimize certain security and privacy risks (Islamet et al., 2015). This paper also describe the
different innovations such as wearable devices, ambient intelligence and big data and their
impacts on the IOT development in the healthcare sectors.
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Methodology:
For conducting valuable information about the chosen topic, only secondary research has
been conducted. Several literatures are studied in order to extract valuable information which
assist to demonstrate the research topic more precisely. Most of the resources are collected
through Web search. There are several online library including the CSU library which are consist
of vast amount of literatures in digital format. Mostly, the literatures are published books, articles
and journals. This literatures provides most authenticated information related with the IOT
development in the healthcare. Some of the websites such as The Guardian and Forbes provide
most updates information about the topic. Vast amount of information is gathered by searching
through several journal, articles and books. However, literatures where the security measurement
of the IOT development is discussed are prioritize than other. The secondary research was
necessary to understand and evaluate the Topic.
Conclusion:
IOT development in the healthcare industry is rapidly growing throughout the world. IOT
applications are showing promising result to enhance the typical tasks and create other
possibilities. For instance, remote monitoring is enhancing the typical monitoring approach
where patients need to meet with the healthcare executives to check and extract the health report.
Even though, the development in the health care center is rapidly involving, some critical issues
is also occurring while development process (Hou & Yeh, 2015). Today’s technologies provide
first transmission of data but the security concerns are still cannot be ignored. Many literatures
provides their explanation about certain security measures which have massive impact on the
healthcare. Most of the healthcare center, stores the patients crucial data into their own database.

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These dataset contains valuable information associated with the patients personal and health
history. As these technologies are engaging with the healthcare sectors, this devices are storing
huge amount of data in them. For instance, smart wear devices generate health report of the user
and also stores this data in them or transfer to cloud. This data can be easily compromised as not
mush of security measures are implemented in those technologies (Islam et al., 2015). This type
of issues are hindering the rapid development of the IOT in health care sector. In this paper, a
research question associated with the IOT was chosen and the topic was discussed in a standard
manner along with literature review. Security concern associated with the IOT development in
the healthcare is a broad topic and need to be highlighted in order to speed up the development
process.
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References:
Bhatt, C., Dey, N., & Ashour, A. S. (Eds.). (2017). Internet of things and big data technologies
for next generation healthcare.
Catarinucci, L., De Donno, D., Mainetti, L., Palano, L., Patrono, L., Stefanizzi, M. L., &
Tarricone, L. (2015). An IoT-aware architecture for smart healthcare systems. IEEE Internet of
Things Journal, 2(6), 515-526.
Da Xu, L., He, W., & Li, S. (2014). Internet of things in industries: A survey. IEEE Transactions
on industrial informatics, 10(4), 2233-2243.
Elhoseny, M., Ramírez-González, G., Abu-Elnasr, O. M., Shawkat, S. A., Arunkumar, N., &
Farouk, A. (2018). Secure medical data transmission model for IoT-based healthcare
systems. IEEE Access, 6, 20596-20608.
Gope, P., & Hwang, T. (2016). BSN-Care: A secure IoT-based modern healthcare system using
body sensor network. IEEE Sensors Journal, 16(5), 1368-1376.
Hou, J. L., & Yeh, K. H. (2015). Novel authentication schemes for IoT based healthcare
systems. International Journal of Distributed Sensor Networks, 11(11), 183659.
Islam, S. R., Kwak, D., Kabir, M. H., Hossain, M., & Kwak, K. S. (2015). The internet of things
for health care: a comprehensive survey. IEEE Access, 3, 678-708.
Laplante, P. A., & Laplante, N. (2016). The internet of things in healthcare: Potential
applications and challenges. IT Professional, (3), 2-4.
Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and
challenges for enterprises. Business Horizons, 58(4), 431-440.
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Li, S., Tryfonas, T., & Li, H. (2016). The Internet of Things: a security point of view. Internet
Research, 26(2), 337-359.
Manogaran, G., Thota, C., Lopez, D., & Sundarasekar, R. (2017). Big data security intelligence
for healthcare industry 4.0. In Cybersecurity for Industry 4.0 (pp. 103-126). Springer, Cham.
Moosavi, S. R., Gia, T. N., Rahmani, A. M., Nigussie, E., Virtanen, S., Isoaho, J., & Tenhunen,
H. (2015). SEA: a secure and efficient authentication and authorization architecture for IoT-
based healthcare using smart gateways. Procedia Computer Science, 52, 452-459.
Patil, H. K., & Seshadri, R. (2014, June). Big data security and privacy issues in healthcare.
In Big Data (BigData Congress), 2014 IEEE International Congress on (pp. 762-765). IEEE.
Sajid, A., Abbas, H., & Saleem, K. (2016). Cloud-assisted IoT-based SCADA systems security:
A review of the state of the art and future challenges. IEEE Access, 4, 1375-1384.
Thota, C., Sundarasekar, R., Manogaran, G., Varatharajan, R., & Priyan, M. K. (2018).
Centralized fog computing security platform for IoT and cloud in healthcare system.
In Exploring the convergence of big data and the internet of things (pp. 141-154). IGI Global.
Tyagi, S., Agarwal, A., & Maheshwari, P. (2016, January). A conceptual framework for IoT-
based healthcare system using cloud computing. In Cloud System and Big Data Engineering
(Confluence), 2016 6th International Conference (pp. 503-507). IEEE.
Yeh, K. H. (2016). A secure IoT-based healthcare system with body sensor networks. IEEE
Access, 4, 10288-10299.
Zhang, Y., Raychadhuri, D., Ravindran, R., & Wang, G. (2013). ICN based Architecture for
IoT. IRTF contribution, October.

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Zhou, W., & Piramuthu, S. (2014, June). Security/privacy of wearable fitness tracking IoT
devices. In Information Systems and Technologies (CISTI), 2014 9th Iberian Conference on(pp.
1-5). IEEE.
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