Secure Integration of Internet-of-Things and Cloud Computing

Abstract

Mobile Cloud Computing is a new technology which refers to an infrastructure where both data storage and data processing operate outside of the mobile device. Another recent technology is Internet of Things. Internet of Things is a new technology which is growing rapidly in the field of telecommunications. More specifically, IoT related with wireless telecommunications. The main goal of the interaction and cooperation between things and objects which sent through the wireless networks is to fulfill the objective set to them as a combined entity. In addition, there is a rapid development of both technologies, Cloud Computing and Internet of Things, regard the field of wireless communications. In this paper, we present a survey of IoT and Cloud Computing with a focus on the security issues of both technologies. Specifically, we combine the two aforementioned technologies (i.e Cloud Computing and IoT) in order to examine the common features, and in order to discover the benefits of their integration. Concluding, we present the contribution of Cloud Computing to the IoT technology. Thus, it shows how the Cloud
Computing technology improves the function of the IoT. Finally, we survey the security challenges of the integration of IoT and Cloud Computing.

Full text

Future Generation Computer Systems 78 (2018) 964–975
Contents lists available at ScienceDirect
Future Generation Computer Systems
journal homepage: www.elsevier.com/locate/fgcs
Secure integration of IoT and Cloud Computing
Christos Stergiou a,Kostas E. Psannis a,∗,Byung-Gyu Kim b,Brij Gupta c
aDepartment of Applied Informatics, School of Information Sciences, University of Macedonia, Thessaloniki, Greece
bDepartment of Information Technology (IT) Engineering at Sookmyung Women’s University, Republic of Korea
cNational Institute of Technology Kurukshetra, India
highlights
•Presentation of IoT and Cloud technologies which focus on security issues.
•Integration benefits of Internet of Things and Cloud Computing technologies.
•Part of AES presented for improvement of security issue, resulting from integration.
•Contribution of AES and RSA algorithms in the integration of IoT and Cloud technologies.
article info
Article history:
Received 5 August 2016
Received in revised form
8 November 2016
Accepted 28 November 2016
Available online 1 December 2016
Keywords:
Internet of Things
Cloud Computing
Mobile Cloud Computing
Security
Privacy
abstract
Mobile Cloud Computing is a new technology which refers to an infrastructure where both data storage
and data processing operate outside of the mobile device. Another recent technology is Internet of Things.
Internet of Things is a new technology which is growing rapidly in the field of telecommunications.
More specifically, IoT related with wireless telecommunications. The main goal of the interaction and
cooperation between things and objects which sent through the wireless networks is to fulfill the
objective set to them as a combined entity. In addition, there is a rapid development of both technologies,
Cloud Computing and Internet of Things, regard the field of wireless communications. In this paper, we
present a survey of IoT and Cloud Computing with a focus on the security issues of both technologies.
Specifically, we combine the two aforementioned technologies (i.e Cloud Computing and IoT) in order
to examine the common features, and in order to discover the benefits of their integration. Concluding,
we present the contribution of Cloud Computing to the IoT technology. Thus, it shows how the Cloud
Computing technology improves the function of the IoT. Finally, we survey the security challenges of the
integration of IoT and Cloud Computing.
©2016 Elsevier B.V. All rights reserved.
1. Introduction
In ntelecommunication fields there is a new technology called
Internet of Things (IoT). The Internet of Things (IoT) is ‘‘the
network of physical objects, devices, vehicles, buildings and other
items which are embedded with electronics, software, sensors,
and network connectivity, permitting these objects to gather and
interchange data’’ [1,2]. IoT technology is the next major step in the
new technology sector, but with the great difference that it carries
massive changes in business functionality. Over the next years, a
flare in the number of connected devices as well as located sites,
and the functions they will perform, is expected.
∗Corresponding author.
E-mail address: kpsannis@uom.edu.gr (K.E. Psannis).
In addition, the main strength of the IoT idea is the high
impact that it will have on several aspects of the everyday-life and
behavior of potential users. The most obvious effects of the Internet
of Things, as a private user could observe, would be visible in both
domestic and working fields. In the first case, some examples of the
possible application scenarios in which the new paradigm, that is
the Internet of Things, will play a leading role in the near future
are domotics, e-health, assisted living, and enhanced learning [3,
4]. In the second case, business users could observe the similar
consequences which are traceable in some fields such as logistics,
intelligent transportation of people and goods, automation and
industrial manufacturing, and business/process management.
The Internet of Things is composed of three main parts:
1. The ‘‘things’’ (objects).
2. The communication networks that connect them.
http://dx.doi.org/10.1016/j.future.2016.11.031
0167-739X/©2016 Elsevier B.V. All rights reserved.

C. Stergiou et al. / Future Generation Computer Systems 78 (2018) 964–975 965
3. The computer systems using data streaming from and to
objects.
For example, home security systems already allow you to check
remotely the locks on your doors, and thermostats in the house. But
what if it was possible to act proactively on your behalf? Imagine
you opened the windows to ventilate your house before arriving,
based on your personal preferences, weather conditions, and the
distance from your house.
To summarize, the Internet of Things is a type of network
of some physical objects or things which, embedded with
software, electronics, sensors and connectivity that enables them,
achieves greater value and service by exchanging data with
manufacturers, operators and some other connected devices [5].
Thus, the intensive computations and the mass storage, which
are supported by clouds, are often inefficient. Some examples
include the limitations of storage, communication capabilities,
energy and processing. Such inefficiencies motivate us to combine
the technology of Mobile Cloud Computing (MCC) and the Internet
of Things. As an emerging technology, Mobile Cloud Computing
integrates multiple technologies for maximizing capacity and
performance of the existing infrastructure [6].
Moreover, there is another technology, called Mobile Cloud
Computing (MCC), which improved through the recent years
by a new generation of services which is made its appearance,
based on the concept of the ‘‘cloud computing’’ which aims to
provide access to the information and the data from anywhere
at any time by restricting or eliminating the need for hardware
equipment [7]. More specifically, Mobile cloud computing is
defined as an integration of cloud computing technology and
mobile devices in order to make mobile devices resourceful
in terms of computational power, memory, storage, energy,
and context awareness. Also, Mobile cloud can be defined as
a contemporary approach to innovative services for firms and
institutions [8]. Mobile cloud computing is the outcome of
interdisciplinary approaches, which consists of mobile computing
and cloud computing [9]. The term mobile cloud is generally
referred to in two perspectives: (a) infrastructure based, and (b)
ad-hoc mobile cloud. In infrastructure based mobile cloud, the
hardware infrastructure remains static, and provides services to
the mobile users. As a result of the operations of Cloud Computing,
it could be used as useful bases for both Internet of Things and
Video Surveillance technologies and could provide improvements
on their functions.
The rest of the paper is organized as follows. In Section 2
there is a review of the related research which deals with the
technology of Internet of Things and Cloud Computing and their
integration. Section 3discusses in detail the technology of Internet
of Things and some of its basic functions. Moreover, Section 4
presents and analyzes the Cloud Computing technique, and its
characteristics. Section 5illustrates the integration of the Internet
of Things technology and the Cloud Computing technology, and
surveys some of their benefits. Finally Section 6provides the
conclusions of the current paper, and offers new possibilities for
the development of future work.
2. Related research review
For the purpose of this paper we study and analyze previous
literature which has been published in the field of cloud computing
and Internet of Things, and their integration. The following
paragraphs present the papers which contributed significantly in
our study.
To begin with, a survey of the different security risks that
pose a threat to the cloud is presented in [10]. Also, in [10]
was given a survey more specific to the different security issues
that has emanated due to the nature of the service delivery
models of a cloud computing system. Moreover, an exploration
of the roadblocks and solutions to provide a trustworthy cloud
computing environment presented in [11]. Cloud computing is an
evolving paradigm with tremendous momentum, but its unique
aspects exacerbate security and privacy challenges.
Concerning the integration of Internet of Things and Cloud
Computing, there have been made some previous studies. A
propose of a new platform for using cloud computing capacities
for provision and support of ubiquitous connectivity and real-time
applications and services for smart cities’ needs is given in [12].
Additionally, a presentation of a framework for data procured
from highly distributed, heterogeneous, decentralized, real and
virtual devices (sensors, actuators, smart devices) that can be
automatically managed, analyzed and controlled by distributed
cloud-based services shown in [12]. In order to realize the full
sharing, free circulation, on-demand use, and optimal allocation of
various manufacturing resources and capabilities, the applications
of the technologies of IoT and CC in manufacturing are investigated
in [13]. Furthermore, a CC- and IoT-based cloud manufacturing
(CMfg) service system (i.e.,CCIoT-CMfg) and its architecture are
proposed, and the relationship among CMfg, IoT, and CC is
analyzed. And finally, the advantages, challenges, and future
works for the application and implementation of CCIoT-CMfg are
discussed in [13]. The [14] mainly focuses on a common approach
to integrate the Internet of Things (IoT) and Cloud Computing
under the name of CloudThings architecture. Also, in [14] review
the state of the art for integrating Cloud Computing and the
Internet of Things, and examine an IoT-enabled smart home
scenario to analyze the IoT application requirements. At the end,
the CloudThings architecture, a Cloud-based Internet of Things
platform which accommodates CloudThings IaaS, PaaS, and SaaS
for accelerating IoT application, development, and management
proposed in [14]. Furthermore, a presentation and discussion about
some of the integration challenges of Iot and Cloud Computing that
must be addressed to enable an intelligent transportation system
to address issues facing the transportation sector such as high fuel
prices, high levels of CO2 emissions, increasing traffic congestion,
and improved road safety are shown in [15].
A presentation of an approach to the development of Smart
Home applications by integrating Internet of Things (IoT) with Web
services and Cloud computing are shown in [16]. The approach
focuses on: (1) embedding intelligence into sensors and actuators
using Arduino platform; (2) networking smart things using Zigbee
technology; (3) facilitating interactions with smart things using
Cloud services; (4) improving data exchange efficiency using JSON
data format. Also, it is shown an implementation of three use
cases to demonstrate the approach’s feasibility and efficiency,
i.e., measuring home conditions, monitoring home appliances,
and controlling home access. The [17] presents a Cloud centric
vision for worldwide implementation of Internet of Things. The
key enabling technologies and application domains that are likely
to drive IoT research in the near future are discussed. A Cloud
implementation using Aneka, which is based on interaction of
private and public Clouds is also presented in [17]. Finally,
it concludes the IoT vision by expanding on the need for
convergence of WSN, the Internet and distributed computing
directed at technological research community. Internet of Things
(IoT) becoming so pervasive that it is becoming important to
integrate it with cloud computing because of the amount of data
IoT’s could generate and their requirement to have the privilege
of virtual resources utilization and storage capacity, but also, to
make it possible to create more usefulness from the data generated
by IoT’s and develop smart applications for the users. This type
of integration is referred to as Cloud of Things in [18]. With
IoTs, anything can become part of the Internet and generate data.

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Moreover, data generated needs to be managed according to its
requirements, in order to create more valuable services. For the
previous purpose, integration of IoTs with cloud computing is
becoming very important. This new paradigm is termed as Cloud
of Things (CoTs) and it is presented in [19]. The [20] focuses in
the attention of the authors on the integration of Cloud and IoT,
which is what we call the CloudIoT paradigm. Also, many works
in literature have surveyed Cloud and IoT separately and, more
precisely, their main properties, features, underlying technologies,
and open issues in [20]. However, these works lack a detailed
analysis of the new CloudIoT paradigm, which involves completely
new applications, challenges, and research issues. The [21] focuses
on some of the key challenges involved in CoT and the proposal
of smart gateway based communication. Cloud of Things, requires
smart gateway to perform the rich tasks and preprocessing, which
sensors and light IoTs are not capable of doing. Finally, the [22]
presents a survey of integration components: Cloud platforms,
Cloud infrastructures and IoT Middleware. In addition, some
integration proposals and data analytics techniques are surveyed
as well as different challenges and open research issues are pointed
out.
Finally, we study integration algorithms and methods about
the aforementioned technologies. In [23] the authors focus on
Fuzzy C-Means based segmentation algorithms because of the
segmentation accuracy they provide. Furthermore, the algorithms
which have been studied need long execution times. Also, the au-
thors of [23] accelerate the execution time of these algorithms us-
ing Graphics Process Unit (GPU) capabilities. At the end, the au-
thors reach the achievement performance enhancement by up to
8.9×without compromising the segmentation accuracy. The main
aim of the [24] is to perform a review of the basic methods used for
such techniques and finding the emerging trends of the research
in this area. The authors of [24] primary focus on summarize some
well-known methods of face recognition in video sequences for ap-
plication in biometric security and enumerate the emerging trends.
The [25] in order to address the challenge of the lack of investigat-
ing on effective and efficient evaluations and measurements for
security and trustworthiness of various social media tools, plat-
forms and applications, surveys the state-of-the-art of social media
networks security and trustworthiness particularly for the increas-
ingly growing sophistication and variety of attacks as well as re-
lated intelligence applications. Also, the authors of [25] highlighted
a new direction on evaluating and measuring the fundamental and
underlying platforms. Furthermore, the authors propose a hierar-
chical architecture for crowd evaluations based on signaling theory
and crowd computing, which is essential for social media ecosys-
tem.
Table 1 lists the findings and the concepts examined in each
paper. In more detail, in Table 1 could observe independently for
each related review that have been studied useful information
related to the year which published, the exact authors, and as a
conclude for each paper the problems and the solutions which they
deal with.
3. Internet of Things
The Internet of Things is a network of devices that transmit,
share, and use data from the physical environment to provide ser-
vices to individuals, corporations, and society. The objects-things
function either individually or in connection with other objects or
individuals, and have unique IDs (identifiers). Also, the Internet of
Things has different applications in health, transport, environment,
energy or types of devices: sensors, devices worn/carried (wear-
able), e.g. watch, glasses, home automation (domotics) (see Fig. 1).
Fig. 1. Internet of Things technology.
3.1. Internet of Things: advantages of the data
What does it mean when the devices and sensors are networked
together and communicate with each other? How can the Internet
of Things affect our daily life? GPS systems, alarm systems, and
thermostats, all send and receive constant feeds to monitor and
automate activities in our daily lives [26]. And the not so obvious:
Mosaic, cups, clothes and other everyday objects can also join
network to send and receive data over the Internet.
Opportunities where the streaming data will create new
markets in order to inspire positive change or to enhance existing
services are examined by businesses. Some examples of sectors
that are at the heart of these developments are listed below [27]:
(a) Smart solution in the bucket of transport: Smart solutions in
the bucket of transport, achieve a reduction of traffic on the
roads, reduce fuel consumption, set priorities in vehicle repair
programs, and save lives.
(b) Smart power grids incorporating more renewable: Smart power
grids incorporating more renewables improve system reliabil-
ity, and reduce the charges consumers, thus providing cheaper
electricity.
(c) Remote monitoring of patients: Remote monitoring of patients
provides easy access to health care, improves the quality of
services, increases the number of people served, and saves
money.
(d) Sensors in homes and airports: Sensors in homes and airports, or
even in your shoes or doors, improve safety by sending signals
when left unused for a certain period of time or when used in
the wrong time.
(e) Engine monitoring sensors that detect & predict maintenance
issues: Engine monitoring sensors that detect and predict
maintenance issues, improve inventory replenishment, and
even define priorities in scheduling maintenance work, repairs,
and regional operations.
3.2. Internet of Things Security
IoT security is the area of endeavor concerned with safeguard-
ing connected devices and networks in the Internet of things. The
Internet of Things involves the increasing prevalence of objects and
entities – known, in this context as things – provided with unique
identifiers and the ability to automatically transfer data over a net-
work. Much of the increase in IoT communication comes from com-
puting devices and embedded sensor systems used in industrial
machine-to-machine (M2M) communication, smart energy grids,

C. Stergiou et al. / Future Generation Computer Systems 78 (2018) 964–975 967
Table 1
Mapping problems against referenced solutions.
Year Author Problems Solutions
2010 H. Takabi
et al. [11]
•Unique aspects exacerbate security and privacy challenges of
Cloud Computing.
•Explores the roadblocks and solutions to providing a
trustworthy Cloud Computing environment.
2011 S. Subashini & V.
Kavitha [10]
•How safe is a Cloud Computing environment is. •A new model targeting at improving features of an existing
model must not risk or threaten other important features of
the current model.
•Enterprise customers are still reluctant to deploy their business in
the cloud.
•Cloud service users need to be vigilant in understanding the
risks of data breaches in this new environment.
•Security is one of the major issues which reduces the growth of
cloud computing and complications with data privacy and data
protection continue to plague the market.
•Different security issues that has emanated due to the
nature of the service delivery models of a cloud computing
system.
2013 J. Gubbi
et al. [17]
•Fueled by the recent adaptation of a variety of enabling wireless
technologies, the IoT has stepped out of its infancy and is the next
revolutionary technology in transforming the Internet into a fully
integrated Future Internet.
•A Cloud centric vision for worldwide implementation of
Internet of Things.
•Cloud implementation using Aneka, which is based on
interaction of private and public Clouds.
•The need for data-on-demand using sophisticated intuitive
queries increases significantly.
•Expanding on the need for convergence of WSN, the Internet
and distributed computing directed at technological research
community.
2013 G. Suciu
et al. [12]
•Cloud Computing and Internet of Things (IoT) are two of the most
popular ICT paradigms.
•A new platform for using cloud computing capacities for
provision and support of ubiquitous connectivity and
real-time applications and services for smart cities’ needs.
•The convergence between cloud computing and IoT has become a
hot topic over the last few years.
•A framework for data procured from highly distributed,
heterogeneous, decentralized, real and virtual devices that
can be automatically managed, analyzed and controlled by
distributed cloud-based services.
2013 J. Zhou et al. [14]•User with a novel means of communicating with the Web world
through ubiquitous object-enabled networks presented by Internet
of Things.
•A common approach to integrate the Internet of Things (IoT)
and Cloud Computing under the name of CloudThings
architecture.
•Cloud Computing enables a convenient, on demand and scalable
network access to a shared pool of configurable computing
resources.
•An IoT-enabled smart home scenario to analyze the IoT
application requirements.
2013 M. Soliman
et al. [16]
•Smart Home minimizes user’s intervention in monitoring home
settings and controlling home appliances.
•An approach to the development of Smart Home
applications by integrating Internet of Things (IoT) with Web
services and Cloud computing.
2014 M. Aazam
et al. [18]
•Everything is going to be connected to the Internet and its data
will be used for various progressive purposes.
•IoT’s and cloud computing integration is not that simple and
bears some key issues. Those key issues along with their
respective potential solutions have been highlighted.
•Internet of Things (IoT) becoming so pervasive that it is becoming
important to integrate it with cloud computing.
2014 M. Aazam
et al. [21]
•Integration of Internet of Things with Cloud Computing is gaining
importance, with the way the trend is going on in ubiquitous
computing world.
•Integration of IoT with Cloud Computing, referred here as
Cloud of Things, requires smart gateway to perform the rich
tasks and preprocessing, which sensors and light IoTs are not
capable of doing.
•Internet of Things (IoT) becoming so pervasive that it is becoming
important to integrate it with cloud computing.
•Focuses on some of the key challenges involved in CoT and
the proposal of smart gateway based communication.
2014 F. Tao et al. [13]•Internet of Things (IoT) and cloud computing (CC) have been
widely studied and applied in many fields, as they can provide a
new method for intelligent perception and connection from M2M,
and on-demand use and efficient sharing of resources, respectively.
•A CC- and IoT-based cloud manufacturing (CMfg) service
system and its architecture are proposed.
•The advantages, challenges, and future works for the
application and implementation of CCIoT-CMfg are discussed.
2015 A. Botta
et al. [20]
•Cloud computing and Internet of Things (IoT) are two very
different technologies that are both already part of our life.
•Integration of Cloud and IoT, which is called the CloudIoT
paradigm.
•A novel paradigm where Cloud and IoT are merged together is
foreseen as disruptive and as an enabler of a large number of
application scenarios.
•A new CloudIoT paradigm, which involves completely new
applications, challenges, and research issues.
2015 J. A. Guerrero
Ibáñez et al. [15]
•Performance of transportation systems is of crucial importance
for individual mobility, commerce, and for the economic growth of
all nations.
•Integration challenges of IoT and CC that must be addressed
to enable an intelligent transportation system to address
issues facing the transportation sector.
•It is imperative to improve the safety and efficiency of
transportation.
2016 M. Diaz
et al. [22]
•Internet of Things comprises many interconnected technologies
like RFID and WSAN in order to exchange information.
•A survey of integration components: Cloud platforms, Cloud
infrastructures and IoT Middleware.
•The limitations of associated devices in the IoT require a
technology like Cloud Computing to supplement this field.
(continued on next page)

968 C. Stergiou et al. / Future Generation Computer Systems 78 (2018) 964–975
Table 1 (continued)
Year Author Problems Solutions
2016 M. Aazam
et al. [19]
•It is becoming very difficult to manage power constrained small
sensors and other data generating devices.
•Integration of IoTs with cloud computing is becoming very
important—Cloud of Things.
•Data generated needs to be managed according to its
requirements, in order to create more valuable services.
•CoTs provide means to handle increasing data and other
resources of underlying IoTs and WSNs.
2016 M. Alsmirat
et al. [23]
•Big revolution in information technology that is used to diagnose
many illnesses and saves patients lives.
•Fuzzy C-Means based segmentation algorithms provide
segmentation accuracy.
•Image segmentation is a mandatory step in many image
processing based diagnosis procedures.
•Accelerate the execution time of Fuzzy C-Means algorithms
using Graphics Process Unit (GPU) capabilities.
2016 B.B. Gupta
et al. [24]
•Face recognition from video has gained attention due to its
popularity and ease of use with security systems based on vision
and surveillance systems.
•Perform a review of the basic methods used for such
techniques and finding the emerging trends of the research in
this area.
•Automated video based face recognition system provides a huge
assortment of challenges as it is necessary to perform facial
verification under different viewing conditions.
•Summarize some well-known methods of face recognition
in video sequences for application in biometric security and
enumerate the emerging trends.
2016 Z. Zhang
et al. [25]
•Social media security and trustworthiness issues have become
increasingly serious.
•Survey on the state-of-the-art of social media networks
security and trustworthiness particularly for the increasingly
growing sophistication and variety of attacks.
•Lack of investigating on effective and efficient evaluations and
measurements for security and trustworthiness of various social
media tools, platforms and applications.
•Highlight a new direction on evaluating and measuring
those fundamental and underlying platforms.
•Propose a hierarchical architecture for crowd evaluations
based on signaling theory and crowd computing.
home and building automation, vehicle to vehicle communication
and wearable computing devices [28,29].
The main problem is that because the idea of networking
appliances and other objects is relatively new, security has not
always been considered in product design. IoT products are often
sold with old and unpatched embedded operating systems and
software. Furthermore, purchasers often fail to change the default
passwords on smart devices—or if they do change them, fail to
select sufficiently strong passwords. To improve security, an IoT
device that needs to be directly accessible over the Internet, should
be segmented into its own network and have network access
restricted. The network segment should then be monitored to
identify potential anomalous traffic, and action should be taken if
there is a problem.
Security experts have warned of the potential risk of large
numbers of unsecured devices connecting to the Internet since
the IoT concept was first proposed in the late 1990s. In December
of 2013, a researcher at Proofpoint, an enterprise security
firm, discovered the first IoT botnet. According to Proofpoint,
more than 25% of the botnet was made up of devices other
than computers, including smart TVs, baby monitors and other
household appliances [28].
3.3. Internet of Things Security model
In the field of Internet of Things technology there are System
models and initial conditions considered are as similar as that
of [30]. A wireless network model with a source–destination pair, N
trusted relays and J eavesdroppers (J≤1)are considered. Assume
that the global CSE is available. The eavesdropper channel, source
encoding schemes, decoding schemes and cooperative protocol are
considered to be public, only source message is assumed to be
confidential. In this paper, the discussion is limited to two main
cooperative schemes: decode-and-forward (DF) and amplify-and-
forward (AF) [31].
Decode-and-forward (DF)
There are two main stages in DF. Source broadcasts its encoded
symbols to its trusted relays using the first transmission slot in
Stage 1. When transmitting the symbol x, the received signals at
the Nrelays are given by,
yr=Psh∗
SRx+nr(1)
where Psis the transmit power of source and nris the noise vector
at relays [31].
In Stage 2, all the trusted relays that successfully decode
the message, re-encode the message and cooperatively transmit
the re-encoded symbols to the destination by using the second
transmission slot. Each relay transmits a weighted version of the
re-encoded symbol. When transmitting the symbol ˜
x, the received
signal at the destination is given by,
yd=hĎ
RDw˜
x+nd(2)
while the received signal at the eavesdroppers is expressed in
vector form as,
ye=HĎ
RE w˜
x+ne.(3)
The transmit power budget for Stage 2 is considered to be P−Ps
where Pis the total power for transmitting one symbol and Psis the
transmit power of source [31].
Amplify-and-forward (AF)
AF is also a two-stage scheme as that of DF. Stage 1 is the same
for both AF and DF, except that the transmit power can be different.
The trusted relays forward the signals that are received during
Stage 1 to the destination, using the second transmission slot in
Stage 2. That is, each relay transmits a weighted version of the noisy
signal that they received during Stage 1. The transmitted signals
of all relays are denoted by the product of diag{w}yr, where wis
the weight vector and yris given by (1). The received signal at the
destination is given by [30],
yd=PshĎ
RDdiag{w}h∗
SRx+hĎ
RDdiag{w}nr+nd.(4)
The received signals at the eavesdroppers, in a vector form, is
denoted by [26],
ye=PsHĎ
RE diag{w}h∗
SRx+HĎ
RE diag{w}nr+ne(5)
where Psis the transmit power of source, nris the noise vector at
relays and xis the received signal. Also, Eqs. (4) and (5) generated
from (1) and (2), and (1) and (3) respectively.
Additionally, another security challenge in IoT is the encryp-
tions algorithm. The RSA algorithm, which is the most commonly
used public key algorithm in the Internet, can be used in sensor
networks with the assistance of a Trusted Platform Module (TPM),
which costs less than 5% of a common sensor node [32]. Thus, the

C. Stergiou et al. / Future Generation Computer Systems 78 (2018) 964–975 969
Fig. 2. Cloud Computing technology.
memory has been measured for a fully authenticated handshake
with 2048-bit RSA keys. This type of handshake has the largest
memory requirements since it needs more code and buffer space
for the client’s Certificate and CertificateVerify messages. The mem-
ory increased its use because the code basically contains hundreds
of statements form buffer[x] = 0xff . The use of this encryption al-
gorithm in IoT’s security could provide better communication pri-
vacy in its functionality.
4. Cloud Computing
Cloud computing provides computing, storage, services, and
applications over the Internet. In general, to render smartphones
energy efficient and computationally capable, major changes
to the hardware and software level are required. This entails
the cooperation of developers and manufacturers. [33]. Mobile
cloud computing is defined as an integration of cloud computing
technology with mobile devices in order to make the mobile
devices resource-full in terms of computational power, memory,
storage, energy, and context awareness. The technology of
Mobile Cloud computing is the outcome of interdisciplinary
approaches combining mobile computing with cloud computing.
Thus, this transdisciplinary domain is also referred as mobile cloud
computing [33].
There are two perspectives in which the term Mobile Cloud
refers: (a) infrastructure based, and (b) ad-hoc mobile cloud. In
the infrastructure based mobile cloud, the hardware infrastructure
remains static and also provides services to the mobile users.
Nevertheless, there are several applications which utilize cloud
resources, but the usage is limited to only storage and application-
specific services such as Apple’s Siri (voice based personal
assistant) and iCloud storage service (see Fig. 2).
4.1. Cloud Computing features
As all technologies, so the Cloud Computing technology has
some features which determine its function. These features are
analyzed and outlined subsequently.
Storage over Internet
Storage over Internet can be defined as a technology framework
that uses Transmission Control Protocol/Internet Protocol (TCP/IP)
networks to link servers and storage devices, and to facilitate
storage solution deployment. The Storage over Internet technology
is also known as Storage over Internet Protocol (SoIP) technology.
With the combination of the best storage and networking industry
approaches, SoIP provides high-performance and scalable IP
storage solutions [34–36].
Service over Internet
The main objective of the Service over Internet is to be
committed to help customers all over the world in order
to transform aspirations into achievements by harnessing the
Internet’s efficiency, speed and ubiquity [34,35].
Applications over Internet
The programs which can be written to do the job of a current
manual task, or virtually anything, and which perform their job
on the server (cloud server) via an internet connection rather
than the traditional model of a program that has to be installed
and run on a local computer are the Cloud Applications, or as
a scientific definition Applications over Internet. Some examples
of powerful programs which run in the cloud and they perform
incredible feats of computing for the oblivious user who only needs
an internet connection and a browser, are google applications,
internet banking, and Facebook [34,35,37].
Energy Efficiency
As a definition, the Energy Efficiency is a way of managing and
restraining the growth in energy consumption. By delivering more
services for the same energy input or for the same services for
less energy input may be something more energy efficient. As an
example, when a Compact Florescent Light (CFL) bulb uses less
energy (1/3–1/5) than an incandescent bulb to produce the same
amount of lights, the Compact Florescent Light (CFL) is considered
to be more energy efficient [34,35,37].
Computationally Capable
The services of computational clouds are leveraging the
computationally intensive and ubiquitous mobile applications
which have been enabled by the technology of Mobile Cloud
Computing. Thus, a system is considered as computationally
capable when it meets the requirements to provide us the results
we want, by making the right calculations [34,35].
4.2. Mobile Cloud Computing trade offs
Mobile Cloud Computing has some disadvantages—limitations
which should be eliminated over the years in order to achieve a
better and more ideal use. A number of businesses, and especially
the smaller ones need to be aware of these limitations before going
in for this technology.
Security
One major issue of the Mobile Cloud Computing is the security
issue. Before someone adopts this technology, they should know
that all the company’s sensitive information would be surrender
to a third-party cloud service provider. This could potentially put
the company in great risk. Hence, someone must be absolutely sure
that they would choose the most reliable service provider, who will
keep the information completely safe [38,39].
Connectivity
Internet connection is critical to Mobile Cloud Computing. Thus,
the user should be certain that there is a good result before opting
for these services. Since someone owes a mobile device which is
connected to the internet has become the norm in the wireless
world of today, Mobile Cloud Computing has a very large potential
user base [40].
Performance
Another major concern of the Mobile Cloud Computing pertains
to its performance. Some users feel performance is not as good as in
native applications. Thus, checking with one service provider and
understanding their track record is advisable [41,42].

970 C. Stergiou et al. / Future Generation Computer Systems 78 (2018) 964–975
Latency (Delay)
In mobile cloud computing, latency (sometimes referred as
turnaround time) is defined as the time involved in offloading
the computation and getting back the results from the nearby
infrastructure or cloud.
Privacy
Data privacy is important and is one of the main bottlenecks
that restrict consumers from adopting mobile cloud computing.
Therefore, to gain consumers trust in the mobile cloud, the
application models must support application development with
privacy protection, and implicit authentication mechanisms [39,
43].
4.3. Mobile Cloud Computing security issues
Cloud computing security or cloud security is an evolving
sub-domain of computer security, network security, and, more
broadly, information security. It refers to a broad set of policies,
technologies, and controls deployed to protect data, applications,
and the associated infrastructure of cloud computing.
Cloud computing and storage solutions provide users and
enterprises with various capabilities to store and process their data
in third-party data centers [44]. Organizations use the Cloud in
a variety of different service models (SaaS, PaaS, and IaaS) and
deployment models (Private, Public, Hybrid, and Community) [45–
47]. There are a number of security concerns associated with
cloud computing. These issues fall into two broad categories:
security issues faced by cloud providers (organizations providing
software, platform, or infrastructure-as-a-service via the cloud)
and security issues faced by their customers (companies or
organizations who host applications or store data on the cloud) [38,
48]. The responsibility is shared, however. The provider must
ensure that their infrastructure is secure and that their clients’
data and applications are protected while the user must take
measures to fortify their application and use strong passwords and
authentication measures.
4.4. Cloud Computing security model
In order to provide secure communication over the network,
encryption algorithm plays an important role. It is a valuable and
fundamental tool for the protection of the data. Encryption algo-
rithm converts the data into scrambled form by using ‘‘a key’’ and
only the user have the key to decrypt the data. Regarding the re-
searches that have been made, an important encryption technique
is the Symmetric key Encryption. In Symmetric key encryption,
only one key is used to encrypt and decrypt the data. In this en-
cryption technique the most used algorithm is the AES [49,50].
AES (Advanced Encryption Standard) is the new encryption
standard recommended by NIST to replace DES algorithm. Brute
force attack is the only effective attack known against it, in which
the attacker tries to test all the characters combinations to unlock
the encryption. The AES algorithm block ciphers. It has variable key
length of 128, 192, or 256 bits; default 256. It encrypts data blocks
of 128 bits in 10, 12 and 14 round depending on the key size. AES
encryption is fast and flexible; it can be implemented on various
platforms especially in small devices. Also, AES has been carefully
tested for many security applications [51,52].
A part of the AES algorithm represented in this work. This
algorithm uses the original key consists of the number of bytes in
any case, which are represented as a 4 ×4 matrix.
Algorithm
Cipher(byte[] input, byte[] output)
{
byte[4,4] State;
copy input[] into State[] AddRoundKey
for (round =1; round <Nr-1; ++round)
{
SubBytes ShiftRows MixColumns AddRoundKey
}
SubBytes ShiftRows AddRoundKey
copy State[] to output[]
}
AES algorithm considered as better than others for a number of
reasons, which is follows [53]:
•AES performs consistently well in both hardware and software
platforms under a wide range of environments. These include
8-bit and 64-bit platforms and DSP’s.
•Its inherent parallelism facilitates efficient use of processor
resources resulting in very good software performance.
•This algorithm has speedy key setup time and good key agility.
•It requires less memory for implementation, making it suitable
for restricted-space environments.
•The structure has good potential for benefiting from instruction-
level parallelism.
•There are no serious weak keys in AES.
•It supports any block sizes and key sizes that are multiples of 32
(greater than 128-bits).
•Statistical analysis of the cipher text has not been possible even
after using huge number of test cases.
•No differential and linear cryptanalysis attacks have been yet
proved on AES.
Additionally, there is an important encryption technique from
the Asymmetric key Encryption. In Asymmetric key encryption,
two keys, private and public keys, are used. Public key is used for
encryption and private key is used for decryption [49,50].
RSA is an Internet encryption and authentication system that
uses an algorithm developed in 1977 by Ron Rivest, Adi Shamir, and
Leonard Adleman. The RSA algorithm is the most commonly used
encryption. Till now it is the only algorithm used for private and
public key generation and encryption. It is a fast encryption [54].
The RSA algorithm which studied in this work uses a key
generator that provides two large primes. Those primes are used
in order to proceed the encryption mode. The two large primes
represent the two types of keys that we use in decryption and
encryption, the public key and the secret key.
Algorithm
Key Generation: KeyGen(p,q)
Input: Two large primes — p,q
Compute n=p.q
ϕ(n)=(p−1)(q−1)
Choose e such that gcd(e, ϕ(n)) =1
Determine dsuch that e.d≡1 mod ϕ(n)
Key:
public key =(e,n)
secret key =(d,n)
Encryption:
c=me mod n
where cis the cipher text and mis the plain text.
RSA has a multiplicative homomorphic property i.e., it is
possible to find the product of the plain text by multiplying the
cipher texts. The result of the operation will be the cipher text of
the product [44].
The equation given ci=E(mi)=miemod n, then we have the
following:
(c1.c2)mod n =(m1.m2)emod n.

C. Stergiou et al. / Future Generation Computer Systems 78 (2018) 964–975 971
5. IoT and Cloud Computing integration
Moreover, a new generation of services, based on the concept
of the ‘cloud computing’, has made its appearance in the last few
years with the purpose of providing access to the information and
the data from any place at any time, thus restricting or eliminating
the need for hardware equipment. The term ‘cloud computation’
is defined as the use of computing logistical resources, as well as
the software level, through the use of services transported over the
Internet. Nowadays, cloud computing services comprise one of the
world’s largest areas of competition between giant companies in
the IT sector and software [55]. Cloud Computing is a technology
which can be set as a base technology in the use of IoT.
More specifically, Mobile Cloud Computing is defined as an in-
tegration of cloud computing technology with mobile devices so
as to make the mobile devices resourceful in terms of computa-
tional power, memory, storage, energy, and context awareness.
Mobile Cloud Computing is the outcome of interdisciplinary ap-
proaches, combining mobile computing and cloud computing [56].
In addition, Cloud computing provides computing, storage, ser-
vices, and applications over the Internet. The technology of Mobile
Cloud Computing is the outcome of interdisciplinary approaches,
combining mobile computing with cloud computing. Thus, this
transdisciplinary domain is also referred as Mobile Cloud Comput-
ing [57].
Some of the main features of the Cloud Computing technology
which relate to the characteristics of both Internet of Things are:
(a) Storage over Internet, (b) Service over Internet, (c) Applications
over internet, (d) Energy efficiency and (e) Computationally
capable. Table 2 lists the features of Mobile Cloud Computing
regarding the convenience this technology offers when combined
with the characteristics of IoT.
Table 2 lists the features of Cloud Computing technology re-
garding the convenience this technology offers. Also, it enumer-
ates the main features of the Internet of Things technology. The
main purpose of Table 2 is to show which of the specific features of
Cloud Computing technology, related more and improve the fea-
tures of Internet of Things technology. As we can observe from Ta-
ble 2, the feature of IoT which affected more by the features of
Cloud Computing is ‘‘Sensors in homes and airports’’. Regarding
the Cloud Computing, the feature which affected more are ‘‘Service
over Internet’’ and ‘‘Computationally capable’’. As a general conclu-
sion, we can observe that those two technologies contribute more
each other in many of their features.
Through the integration of IoT and Cloud we have the
opportunity to expand the use of the available technology that
provided in cloud environments. Applications and information that
use the Internet of Things technology with this integration can be
used through the cloud storage. The integration of IoT and Cloud
technologies represented in Fig. 3. The cloud offers to mobile and
wireless users to access all the information and the application that
needed for the IoT connectivity.
5.1. Security issues in IoT and Cloud Computing integration
There is a rapid and independent evolution considering the two
words of IoT and Cloud Computing. To begin with, the virtually
unlimited capabilities and resources of Cloud Computing in order
to compensate its technological constrains, such as processing,
storage and communication, could be a benefit for the Internet
of Things technology [58]. Also, the IoT technology extends its
scope to deal with real world things in a more distributed and
dynamic manner and by delivering new services in a large number
of real life scenarios, might be beneficial for the use of Cloud
Computing technology. In many cases, Cloud can provide the
intermediate layer between the things and the applications, hiding
Fig. 3. IoT & Cloud Computing integration.
all the complexity and functionalities necessary to implement the
latter [20].
Through the integration of IoT and Cloud Computing could
be observed that Cloud Computing can fill some gaps of IoT
such the limited storage and applications over internet. Also, IoT
can fill some gaps of Cloud Computing such the main issue of
limited scope. Based in motivations such those referred previously
and the important issue of security in both technologies we can
consider some drivers for the integration. The security issue of this
integration has a serious problem. When critical IoT applications
move towards the Cloud Computing technology, concerns arise
due to the lack of trust in the service provider or the knowledge
about service level agreements (SLAs) and knowledge about the
physical location of data. Consequently, new challenges require
specific attention as mentioned in surveys [59–61]. Multi-tenancy
could also compromise security and lead to sensitive information
leakage. Moreover, public key cryptography cannot be applied at
all layers due to the computing power constraints imposed by
the things. These are examples of topics that are currently under
investigation in order to tackle the big challenge of security and
privacy in Cloud Computing and IoT integration [20].
Subsequently, some challenges about the security issue in the
integration of two technologies are listed [20].
(a) Heterogeneity. A big challenge in Cloud Computing and IoT
integration is related to the wide heterogeneity of devices,
operating systems, platforms, and services available and
possibly used for new or improved applications [62].
(b) Performance. Often Cloud Computing and IoT integration’s ap-
plications introduce specific performance and QoS require-
ments at several levels (i.e. for communication, computation,
and storage aspects) and in some particular scenarios meeting
requirements may not be easily achievable [63,64].
(c) Reliability. When Cloud Computing and IoT integration is
adopted for mission-critical applications, reliability concerns
typically arise e.g., in the context of smart mobility, vehicles
are often on the move and the vehicular networking and
communication is often intermittent or unreliable. Often
intermittent or unreliable. When applications are deployed in
resource constrained environments a number of challenges
related to device failure or not always reachable devices
exists [65].

972 C. Stergiou et al. / Future Generation Computer Systems 78 (2018) 964–975
Table 2
Contributions of Cloud Computing in internet of things.
Internet of things characteristics Storage over
Internet
Service over
Internet
Applications over
Internet
Energy
efficiency
Computationally
capable
Smart solution in the bucket of transport × × × ×
Smart power grids incorporating more renewable × × × ×
Remote monitoring of patients × × ×
Sensors in homes and airports × × × × ×
Engine monitoring sensors that detect & predict maintenance issues × × × ×
(d) Big Data. With an estimated number of 50 billion devices that
will be networked by 2020, specific attention must be paid
to transportation, storage, access, and processing of the huge
amount of data they will produce. The ubiquity of mobile
devices and sensor pervasiveness, indeed call for scalable
computing platforms [66].
(e) Monitoring. As largely documented in the literature, monitor-
ing is an essential activity in Cloud environments for capacity
planning, for managing resources, SLAs, performance and se-
curity, and for troubleshooting [67].
Table 3 lists the two technologies that we study in this paper
and the challenges of their integration that arising from our study.
These challenges related to the security issue in the integration
of two aforementioned technologies and they listed in detailed in
Section 5.1. As we can observe from Table 3, the both technologies
have two common main challenges of their integration which
are Performance and Big Data. Additionally, we can observe that
Internet of Things technology related to more challenges (4) than
the Cloud Computing technology (3).
5.2. Proposed efficient IoT and Cloud Computing security model
As we can infer, by taking advantage of the reasons which AES
algorithm provides better secure in Cloud Computing and the two
models that give benefits in security issues in IoT we can propose
a new method that uses those benefits in order to improve the
security and privacy issues in the integration of two technologies.
The AES algorithm provides the ability to have speed key
setup time a good key agility. So, if we use this algorithm in the
functionality of DF model, we could have a trusted relay method
with an encryption of a speed key setup. Therefore, instead the
trust relay use that DF and AF methods provide we can seize
also there no serious weak keys in AES and so we could have a
beneficial security use of the encryption in the integrated new
model. Moreover, we can take advantage the less memory which
AES needs for implementation that makes it for restricted-space
environments. Thus, we can seize the transmit power that the AF
model provides and as a result we can have a better and more
trusted transmission. In the way of transmission, when the symbol
˜
xtransmitted with the use of DF model, the received signal at
destination is given by the Eq. (2), which mentioned in previous
section.
With this proposed model we can extend the advances of
Internet of Things and Cloud Computing, by developing a highly
innovative and scalable service platform to enable secure and
privacy services. Through this research we can propose the
following algorithm which extends the security advances of both
technologies.
Key Generation: KeyGen(p,q)
Input: Two large primes — p,q
Compute n=p.q
buffer(n)=(p−1)(q−1)
Choose esuch that gcd(e,buffer(n)) =1
In which algorithm the equation method that contains hun-
dreds of statements of the form buffer[x] = 0xff is combined. With
the use of this new type of RSA algorithm in the encryption process,
we can conclude that a higher level of communications’ security
can be provided in the functionalities of the IoT.
Key:
public key =(e,n)
secret key =(d,n)
Encryption:
c=me mod n
where cis the cipher text and mis the plain text.
Also, as a proposal of this work could be the following part of
algorithm which uses the original key consists of 128 bits/16 bytes
which are represented as a 4 ×4 matrix. With the use of this part of
AES algorithm we can draw that data which encrypted with 128 bit
(or 16 bytes) can be have better encrypted as an 4 ×4 matrix in
order of providing a better use of communication privacy.
Cipher(byte[] input, byte[] output)
{
byte[4,4] State;
copy input[] into State[] AddRoundKey
for (i=4;i<44;i++)
{
T=W[i−1];
if (imod 4 == 0)
T=Substitute (Rotate (T)) XOR RConstant [i/4];
W[i] = W[i−4]XOR T;
SubBytes ShiftRows MixColumns AddRoundKey
}
SubBytes ShiftRows AddRoundKey
copy State[] to output[]
}
Table 4 lists the key characteristics of the two encryption
algorithms which have been studied and used in order to use them
for the experimental proposal. The key characteristic which is more
important is their Speed in which both algorithms are very fast.
The key characteristic in which there is a relative difference is the
Rounds, where AES needs 10, 12 or 14 rounds instead of the RSA
that needs only 1.
5.3. Experimental results
Considering the benefits of the security models and algorithms
of Internet of Things and Cloud Computing technologies we
can observe that we can have a beneficial use of integration
those two technologies. Instead of the wide use of IoT we
can take advantage that Cloud Computing security through the
AES algorithm performs consistently well in both hardware and
software platforms under a wide range of environments. This use
could be possible for all type of platforms and DSPs. Furthermore,
the new integrated technology could has good potential for
benefiting from instruction-level parallelism and will support any
type of block sizes and key sizes that are multiples of 32 and
used both of IoT and Cloud Computing. Also, each transmitted
signal through the new technology can transmitted as a relay and

C. Stergiou et al. / Future Generation Computer Systems 78 (2018) 964–975 973
Table 3
Affects of IoT & Cloud Computing security challenges.
IoT & Cloud Computing security challenges Heterogeneity Performance Reliability Big data Monitoring
Internet of Things × × × ×
Cloud Computing × × ×
Table 4
Comparison of AES and RSA algorithms.
Characteristics Developed Key length Rounds Certifications Speed
AES 1998 128, 192 or 256 bits 10, 12 or 14 AES winner, CRYPTREC, NESSIE, NSA Very fast
RSA 1977 1024–4096 bits 1 PKCS#1, ANSI X9.31, IEEE 1363 Very fast
Table 5
AES contribution in IoT and Cloud Computing.
AES characteristics Key length Rounds Certifications Speed
Internet of Things × × ×
Cloud Computing × × ×
IoT & CC integration × × × ×
Table 6
RSA contribution in IoT and Cloud Computing.
RSA characteristics Key length Rounds Certifications Speed
Internet of Things × × ×
Cloud Computing × × ×
IoT & CC integration × × × ×
trusted signal with a weighted version of the re-encoded symbol.
By the use of RSA algorithm we can take advantage the two keys
encryption in order to provide better secure in the use of the new
model.
Through this integration we can achieve some useful functions,
i.e. we can use the Cloud-based IoT service in order to connect
sensors and also made them capable to share the sensor readings
with others, reducing the security issues. Furthermore, another
useful function is that we can use the HTTP protocol in order
to send data between IoT things and the Cloud Computing
applications. Moreover, some of the key advantages and challenges
that can be defined from this integration are: (1) Both the physical
hardware manufacturing resource and software manufacturing
can be intelligently perceived and connected into the wider
networks with the support of IoT technologies. (2) The collected
information and data can be communicated and transmitted
between M2M under the support of specific IoT technologies. (3)
The collected and transmitted information can be processed and
computed according to specific requirements under the support
of different Cloud Computing service, and some useful data and
decision information can be intelligently generated and obtained.
However, many other challenges and other benefits remains
to be addressed through the integration of Internet of Things and
Cloud Computing regarding the security issues, but also regarding
the hole use of both technologies together.
The Tables 5 and 6exhibiting the key characteristic of
the two encryption algorithms that used in order to achieve
integration of the technologies of IoT and Cloud Computing
concerning the security issue. Table 5 presents which of the
key characteristics of AES encryption algorithm contributes both
IoT and Cloud Computing technologies, and at the end how
completely contributes the integration model of IoT and Cloud
Computing. Subsequently, Table 6 presents which of the key
characteristics of RSA encryption algorithm also contributes both
IoT and Cloud Computing technologies, and at the end how
completely contributes the integration model of IoT and Cloud
Computing too.
6. Conclusion
The Cloud Computing technology offers many possibilities, but
also places several limitations as well. Cloud Computing refers
to an infrastructure where both the data storage and the data
processing happen outside of the mobile device. In this paper,
we present a survey of Internet of Things Technology, with an
explanation of its operation and use. Moreover, we present the
main features of the Cloud Computing and its trade offs. Cloud
Computing refers to an infrastructure where both data storage and
data processing happen outside of the mobile device. Also, the
Internet of Things is a new technology which is growing rapidly
in the field of telecommunications, and especially in the modern
field of wireless telecommunications.
The main goal of the interaction and cooperation between
things and objects sent through the wireless networks is to fulfill
the objective set to them as a combined entity. In addition, based
on the technology of wireless networks, both the technologies
of Cloud Computing and Internet of Things develop rapidly. In
this paper, we present a survey of IoT and Cloud Computing with
a focus on the security issues of both technologies. Specifically,
we combine the two aforementioned technologies (i.e. Cloud
Computing and IoT) in order to examine the common features, and
in order to discover the benefits of their integration. Concluding,
the contribution of Cloud Computing to the technology IoT, and
it shows how the Cloud Computing technology improves the
function of the IoT was presented. At the end, the security
challenges of the integration of IoT and Cloud Computing were
surveyed through the proposed algorithm model, and also there is
a presentation of how the two encryption algorithms which were
used contributes in the integration of IoT and Cloud Computing.
This can be the field of future research on the integration of
those two technologies. Regarding the rapid development of both
technologies the security issue must be solved or reduced to
a minimum in order to have a better integration model. These
security challenges that surveyed in this paper could be the sector
for further research as a case study, with the goal of minimizing
them.
Acknowledgments
The authors would like to thank the anonymous reviewers
for their valuable comments and feedback which was extremely
helpful in improving the quality of the paper.
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Christos Stergiou was born in Thessaloniki, Greece. Cur-
rently, he is an undergraduate student in the Department
of Applied Informatics, School of Information Sciences,
University of Macedonia, Greece. Christos received a de-
gree in Informatics and Computer Engineering from Tech-
nological Educational Institute of Western Macedonia, An-
nex of Kastoria (Greece); an M.Sc. degree in Wireless Com-
munication Systems from the Department of Technician of
Wired and Wireless Networks of Brunel University (UK).
Kostas E. Psannis was born in Thessaloniki, Greece. Kostas
received a degree in Physics from Aristotle University
of Thessaloniki (Greece), and the Ph.D. degree from the
Department of Electronic and Computer Engineering of
Brunel University (UK). From 2001 to 2002 he was
awarded the British Chevening scholarship sponsored
by the Foreign & Commonwealth Office (FCO), British
Government. He was awarded, in the year 2006, a
research grant by IISF (Grant No. 2006.1.3.916). Since
2004 he has been a (Visiting) Assistant Professor in
the Department of Applied Informatics, University of
Macedonia, Greece, where currently he is Assistant Professor (& Departmental
LLP/Erasmus-Exchange Students Coordinator and Higher Education Mentor) in
the Department of Applied Informatics, School of Information Sciences. He is
also joint Researcher in the Department of Scientific and Engineering Simulation,
Graduate School of Engineering, Nagoya Institute of Technology, Japan. He
has extensive research, development, and consulting experience in the area
of telecommunications technologies. Since 1999 he has participated in several
R&D funded projects in the area of ICT (EU and JAPAN). Kostas Psannis was
invited to speak on the EU-Japan Co-ordinated Call Preparatory meeting, Green &
Content Centric Networking (CCN), organized by European Commission (EC) and
National Institute of Information and Communications Technology (NICT)/Ministry
of Internal Affairs and Communications (MIC), Japan (in the context of the
upcoming ICT Work Programme 2013) and International Telecommunication
Union (ITU) SG13 meeting on DAN/CCN, July 2012, amongst other invited
speakers. He has several publications in international Conferences, books chapters
and peer reviewed journals. His professional interests are: Multimodal Data
Communications Systems, Haptic Communication between Humans and Robots,
Cloud Transmission/Streaming/Synchronization, Future Media - Internet of Things,
Experiments on International Connections (E-ICONS) over TEIN3 (Pan-Asian),
Science Information Network (SINET, Japan), GRNET (Greece)-Okeanos Cloud, and
GEANT (European Union) dedicated high capacity connectivity. He is Guest Editor
for the Special Issue on Architectures and Algorithms of High Efficiency Video
Coding (HEVC) Standard for Real-Time Video Applications (2014), Journal of Real
Time Image Processing (Special Issue). He is Guest Editor for the Special Issue
on Emerging Multimedia Technology for Smart Surveillance System with IoT
Environment (2016), The Journal of Supercomputing (Special Issue). He is Guest
Editor for the Special Issue on Emerging Multimedia Technology for Multimedia-
centric Internet of Things (mm-IoT) (2016), Multimedia Tools and Applications
(Special Issue). He is currently GOLD member committee of IEEE Broadcast
Technology Society (BTS) and a member of the IEEE Industrial Electronics Society
(IES). He is also a member of the European Commission (EC) EURAXESS Links JAPAN
and member of the EU-JAPAN Centre for Industrial Cooperation.
Byung-Gyu Kim has received his B.S. degree from Pusan
National University, Korea, in 1996 and an M.S. degree
from Korea Advanced Institute of Science and Technology
(KAIST) in 1998. In 2004, he received a Ph.D. degree in
the Department of Electrical Engineering and Computer
Science from Korea Advanced Institute of Science and
Technology (KAIST). In March 2004, he joined in the
real-time multimedia research team at the Electronics
and Telecommunications Research Institute (ETRI), Korea
where he was a senior researcher. In ETRI, he developed
so many real-time video signal processing algorithms and
patents and received the Best Paper Award in 2007. From February 2009 to
February 2016, he was associate professor in the Division of Computer Science
and Engineering at SunMoon University, Korea. In March 2016, he joined the
Department of Information Technology (IT) Engineering at Sookmyung Women’s
University, Korea where he is currently an associate professor. In 2007, he served
as an editorial board member of the International Journal of Soft Computing, Recent
Patents on Signal Processing, Research Journal of Information Technology, Journal
of Convergence Information Technology, and Journal of Engineering and Applied
Sciences. Also, he is serving as an associate editor of Circuits, Systems and Signal
Processing (Springer), The Journal of Supercomputing (Springer), The Journal of
Real-Time Image Processing (Springer), The Scientific World Journal (Hindawi),
and International Journal of Image Processing and Visual Communication (IJIPVC).
He also served as Organizing Committee of CSIP 2011 and Program Committee
Members of many international conferences. He has received the Special Merit
Award for Outstanding Paper from the IEEE Consumer Electronics Society, at IEEE
ICCE 2012, Certification Appreciation Award from the SPIE Optical Engineering in
2013, and the Best Academic Award from the CIS in 2014. He has been honored
as an IEEE Senior member in 2015. He has published over 150 international
journal and conference papers, patents in his field. His research interests include
software-based image and video object segmentation for the content-based
image coding, video coding techniques, 3D video signal processing, wireless
multimedia sensor network, embedded multimedia communication, and intelligent
information system for image signal processing. He is a senior member of IEEE and
a professional member of ACM, and IEICE.
Brij Gupta received Ph.D. degree from Indian Institute
of Technology Roorkee, India in the area of Information
and Cyber Security. He has published more than 90 re-
search papers (including 03 book and 14 chapters) in Inter-
national Journals and Conferences of high repute includ-
ing IEEE, Elsevier, ACM, Springer, Wiley Inderscience, etc.
He has visited several countries, i.e. Canada, Japan, China,
Malaysia, Hong-Kong, etc. to present his research work.
His biography was selected and publishes in the 30th Edi-
tion of Marquis Who’s Who in the World, 2012.
He is also working principal investigator of various
R&D projects. He is serving as associate editor of IEEE Access, Associate editor of
IJICS, Inderscience and Executive editor of IJITCA, Inderscience, respectively. He is
also serving as reviewer for Journals of IEEE, Springer, Wiley, Taylor & Francis, etc.
Currently he is guiding 10 students for their Master’s and Doctoral research work in
the area of Information and Cyber Security. He is also serving as guest editor of vari-
ous reputed Journals. Dr. Gupta is also holding position of editor of various Interna-
tional Journals and magazines. He has also served as Technical program committee
(TPC) member of more than 20 International conferences worldwide. Dr. Gupta is
member of IEEE, ACM, SIGCOMM, The Society of Digital Information and Wireless
Communications (SDIWC), Internet Society, Institute of Nanotechnology, Life Mem-
ber, International Association of Engineers (IAENG), Life Member, International As-
sociation of Computer Science and Information Technology (IACSIT). He was also
visiting researcher with Yamaguchi University, Japan in January, 2015. His research
interest includes Information security, Cyber Security, Mobile/Smartphone, Cloud
Computing, Web security, Intrusion detection, Computer networks and Phishing.