Smart Home based on Internet of Things and Ethical Issues
Victor Chang
, Zhi Wang
, Qianwen Ariel Xu
, Lewis Golightly
, Ben S. Liu
and Mitra Arami
Artificial Intelligence and Information System Research Group, School of Computing,
Engineering and Digital Technologies, Teesside University, Middlesbrough, U.K.
IBSS, Xi’an Jiaotong-Liverpool University, Suzhou, China
Department of Marketing, Quinnipiac University, U.S.A.
EM Normandie Business School, France,
Keywords: Smart Home, Ethics, Internet of Things, Data Analytics.
Abstract: With the growing popularity of the Internet of Things, smart home applications are developing gradually and
bring convenience to users' lives. In this paper, first, an overview of IoT and widely agreed and accepted
three-layer architecture of IoT are introduced. Next, this paper discusses the basic features of the smart home
and data analytics in a smart home with the benefits and analysis process. Security and privacy are the key
ethical problems in the smart home, such as security attack, analysis of "non-sensitive" data, improper
information collection and data abuse. Additionally, the user perception of privacy issues is included in this
paper. Furthermore, this paper recommends suitable suggestions for improving ethical issues.
The Internet of Things (IoT) is a crucial component
of emerging information technologies and an
extension of Internet applications. Automated work
and connection of devices used in daily life via the
Internet are the basic concepts behind IoT (Burhan et
al., 2018). Data from the physical world collected by
devices attached to each object is processed and
analyzed and finally used to perform the actions. IoT
has covered many areas, such as the health care
domain, smart home, smart transportation,
infrastructure management, etc. (Burhan et al., 2018).
This paper will focus on smart home, which brings
ordinary home the characteristics of intelligence,
remote control and interconnection. It is one of the
most representative components in the IoT era
(Yassin et al., 2019). Apart from the introduction of
the IoT and smart home, ethical issues, such as
security and privacy, and the suggestions will be
discussed in this article.
2.1 Introduction of IoT
The meaning of the IoT is a vast network connected
by a variety of objects or processes through various
information sensing devices for intelligent
recognition, positioning, tracker, surveillance, and
management with the presence of the Internet (Leng
et al., 2020). The aim of the IoT is to connect all
physical things in communication so that they can be
integrated with computer-based systems more
directly and the identification, management, and
control can be simplified. (De Cremer, Nguyen &
Feamster, 2017). The Internet of Things can bring
benefits and services to individuals, businesses and
societies by capturing and analyzing data from
sensors at the endpoints of connected devices and
combining these data (Nguyen and De Cremer, 2016).
Furthermore, IoT improves comfort and efficiency
through collaboration between smart objects
(Risteska Stojkoska & Trivodaliev, 2017). It can be
applied in numerous aspects, including personal
health, public safety, industrial monitoring,
intelligent transportation, environmental protection
Chang, V., Wang, Z., Xu, Q., Golightly, L., Liu, B. and Arami, M.
Smart Home based on Internet of Things and Ethical Issues.
DOI: 10.5220/0010178100570064
In Proceedings of the 3rd International Conference on Finance, Economics, Management and IT Business (FEMIB 2021), pages 57-64
ISBN: 978-989-758-507-4
2021 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
Figure 1: Three-layer architecture of IoT.
and other fields. For example, in the manufacturing
field, the equipment can be remotely monitored,
upgraded and maintained from a long distance away
by installing IoT based sensors on the equipment.
Moreover, the equipment manufacturers are able to
learn the use of the products in a better way, collect
the data of the product life cycle completely, thereby
guiding the product design and after-sales service
(Lee and Fumagalli, 2019).
2.2 IoT Layered Architectures
Building a capable IoT architecture is beneficial to
the fast, reliable, and secure integration of
information technology and communication
technologies (Kumar & Mallick, 2018). In general, as
is shown in Fig. 1, the architecture of the IoT has three
layers, namely, the perception layer, the network
layer and the application layer.
The three-layer architecture is a fundamental and
widely agreed architecture proposed at the beginning
of the development of IoT (Burhan et al., 2018).
The perception layer is named the sensing layer as
well, whose feature is to identify objects and gather
environmental data. It contains a variety of sensors,
consisting of RFID tags and readers, temperature and
humidity sensors, Global Positioning System,
cameras, infrared, two-dimensional code tags, as well
as other sensing terminals. It is similar to the role of
skin and facial features in the human body structure.
The network layer is the whole IoT’s hub, which is in
charge of the transmission and processing of data
obtained by the perception layer with the internet
connectivity of devices (Kumar & Mallick, 2018). It
contains a number of networks, consisting of the
Internet, WAN, a network management system, and a
cloud computing platform. The network layer is
similar to the nerve center and brain of the human
body structure. The application layer is the interface,
which connects the IoT with users. Its primary
function is to analyze and process the information
from the network layer, make correct control and
decision, and realize intelligent management
applications and services.
A smart home (SH) is an essential application of IoT
and it comes into the picture to control and monitor
the home (Geneiatakis et al., 2017). The trends of
search popularity since 2013 for the terms: smart
home, IoT are shown in Fig. 2. It is demonstrated that
there is an increasing trend for smart home and IoT,
according to Fig. 2. By combining different kinds of
IoT based, the smart home provides a variety of
functions, e.g., lighting control, household appliances
control, telephone remote control and others (Alaa et
al.,2017). Compared to conventional homes, the
smart home has ordinary residential functions and is
also equipped with functions of home establishment,
networking, intelligent appliances, and equipment
automation. Additionally, all-around interaction
capabilities are provided, and even related costs are
reduced on various energy consumption (Marikyan et
al., 2019).
Figure 2: Interest over time according to Google trends
since 2013 for terms: Smart home and IoT.
FEMIB 2021 - 3rd International Conference on Finance, Economics, Management and IT Business
Table 1: Features of Smart Home.
air conditioning control, network appliances, lighting systems, digital cinema
systems, security systems, audio and video equipment, curtain control, etc.
home appliance control, lighting control, telephone remote control, indoor and
outdoor remote control, burglar alarm, environmental monitoring, infrared
forwarding and programmable timing control, etc.
Referring to Table 1, under the notion of SH, there are
some important components, and a brief introduction
to some of them is given. One is home automation, an
essential system of the SH. It refers to integrating or
controlling electronic appliances in the house
(MIHALACHE, 2017), consisting of systems of
lighting, security, video and audio, computer
equipment, heating, and air-conditioning. A Central
Processor Units is set to receive the data from
electronic and electrical devices and then send
specific information to other devices with some
procedures. It can control the devices by using
interfaces like mobile phones, remote controllers,
computers, etc. Home Network is also a vital part of
the SH. It is a family information platform that links
the PCs, household electrical appliances, safety
systems, lighting systems and WAN in smart homes,
implements equipment management, and data and
multimedia information sharing (Tetteh &
Amponsah, 2020).
4.1 Benefits of Data Analytics in Smart
Through intelligent devices linked to the IoT system,
SH can generate a massive amount of data (El-Sayed
et al., 2018). In the face of data with information, how
to transmit, store, analyze, and apply, it is a
tremendous opportunity and challenge in the current
era for the smart home. Analyzing these data in
almost real-time or off-line has a significant effect on
the economy, health, and safety of the society, as the
useful information implicit in the data can be derived
(Yassine et al., 2019). Take an example mentioned in
Yassine's paper (2019)- manufacturers can
continuously analyze the data of devices under the
permission of IoT applications and then take
measures to develop equipment maintenance plans or
replace faulty equipment immediately. It can be
revealed that data analytics in a smart home can
summarize the behavior rules of smart home
occupants and it can enhance the convenience and
efficiency of daily life.
4.2 Data Analysis Process in Smart
The paper will briefly introduce a kind of big general
data analysis and recommendation for SH (Rathore et
al., 2017). The SH generates an enormous amount of
data with different formats, sources and periods
because various types of sensors produce them. As
the raw data is messy and has much more metadata
than actual measurements, it is necessary to apply
registration and filtering technology to filter
unnecessary metadata and discard the repeated data.
Then, by using different communication technologies
through the Internet, the data is transmitted from the
relay towards the gateway node, and then from the
base station to the internet cloud. Tightly related data
can be grouped into a collection, which can be
processed more effectively. Afterward, it is filtered
and classified using different algorithms. After
passing through the transformer, preprocessed data
will be stored in the database and processed (such as
statistical analysis, professional computing, and data
mining) in a stable system. Finally, the interpretation,
prediction, and visualization results are used to make
smart home applications and reports generated
intelligently. During this process, the quality and
availability of the data should also be considered, as
well as the privacy-protecting-and-detecting
environment (Lee, 2018). See Fig. 3.
Apart from the benefits of data analytics for smart
homes, smart home raises substantial ethical issues in
different ways and aspects when analyzing and
applying data. The problems have aroused public
Smart Home based on Internet of Things and Ethical Issues
Figure 3: The IoT-based big data analysis process.
applying data. The problems have aroused public
attention, including individuals, companies and the
government. In the following paper, the basic
concepts, ethical issues and the threats they pose will
be discussed.
5.1 Security and Privacy Threats
Among the ethical issues in smart homes, data
security and personal privacy are the most important
and concerning issues (Guo et al., 2019; Butun et al.,
2019). A considerable amount of sensitive personal
information is collected by sensors from the
occupant's private space and is transmitted through
the Internet. Security is related to data protection from
tampering, alteration, or disclosure for incidental or
malicious reasons. Privacy mentioned in this paper is
the appropriate collection, analysis and sharing of
personal data (Shave, 2018). The two concepts will
be discussed together in this article as they are
5.1.1 CIA Triad Model
While speaking of information security or data
security, the basic concept of information security
CIA should be introduced, whose principle is to
ensure data protection and information systems
(Shave, 2018). CIA is short for Confidentiality,
Integrity and Availability (Zheng et al., 2014).
Confidentiality refers to prevent the data from being
accessed by unauthorized users. In order to maintain
confidentiality, several protective approaches like
encryption or permission are often implemented
when processing, transmitting and storing data for
security control. The integrity of information refers to
that the original data should be prevented from being
changed arbitrarily during the process of data storage
or transmission. Consequently, to maintain integrity,
strict control is required on the identity authentication
and data access. The availability of information
stands for the information available to the legitimate
owners and users of the information in a timely
manner and whenever they need it (Shave, 2018). The
core of information security is to make sure that the
raw data can be timely and securely transferred or
stored between its legal owners and users without
being destroyed. It cannot be obtained or changed by
those who should not obtain them.
5.1.2 Security Attacks
One of the troubles about security and privacy in the
SH is the unknown vulnerabilities. With the
innovation and development of big data storage,
computing and analysis, it has driven a new
revolution in the software and hardware architecture
of information systems. Following this trend, smart
home appliances are continuously being updated. It
may introduce unknown vulnerabilities in software,
hardware, protocols and devices because the speed of
discovering and fixing vulnerabilities is not keeping
up with the speed of updating. The existing security
protection technologies cannot withstand the security
risks of unknown vulnerabilities. Simultaneously, the
development of big data technology has spawned a
new type of advanced cyber-attack. Hackers can
maximize the collection of useful information, such
as phone calls, home addresses, even private
information within the family to prepare for attacks
and make attacks more accurate. Hacking and
unauthorized access can pose one of the most direct
threats to personal privacy in a smart home
environment. Unknown vulnerabilities combined
with new cyberattacks make intelligent home systems
vulnerable to attacks, causing serious security and
privacy concerns. According to Geneiatakis et al.'s
(2017) analysis, eavesdropping, simulation, DoS, and
software development attack vectors can pose serious
privacy hazards to existing smart home IoT
infrastructure under certain conditions. The emerging
threats of security and privacy will be divided into
three parts under the three-layer architecture. This
paper will mainly focus on the perception layer.
FEMIB 2021 - 3rd International Conference on Finance, Economics, Management and IT Business
First of all, security threats in the perception layer
are mainly carried out in the following three ways:
Physical Attack: The attacker implements
physical damage to prevent the IoT terminal
from performing properly or stealing terminal
equipment and generating users' sensitive data
by cracking.
Eavesdropping: Eavesdropping is a means of
network attack. It is to steal data resources and
sensitive data by a variety of feasible legal or
illegal approaches in real-time. In a smart home,
to manage it, users generally adopt two
interactive modes to interact with IoT devices
through different platforms such as personal
computers, smartphones, and tablets. One
modality is to use the hub's connectivity and
services directly and the other is to access
Internet cloud services, which are interrelated
with IoT hubs and linked IoT devices
(Geneiatakis et al., 2017). During this process,
an attacker can intercept information
transmitted via a network, which means that
eavesdropping happens. For example, hackers
can use security holes to watch real-time home
surveillance video. They can obtain a large
amount of personal privacy information by
monitoring videos, such as the living habits and
behavior patterns of the occupants.
Simulation Attack: Through deceiving the
communication system (or user), illegal users
are disguised as rightful users or privileged
users. Then, attackers can control the smart
home system and extract sensitive information
from it; that is to say, hackers can have the same
permissions as the owner and can operate
various smart home components. This kind of
active attack affects the user's privacy and the
confidentiality of the services provided and
influences data integrity (Geneiatakis, 2017).
Second, in the network layer, there are also
several kinds of security threats, including DoS
Attack, Storage Attack, Exploit Attack and Fake base
station attack. Among them, Dos Attack and Exploit
Attack are introduced as follows:
Denial of Service Attack (DoS): The most
frequent means of a denial of service attacks is
to use legitimate service requests to occupy too
many service resources, thereby overloading the
server and making it unable to respond to other
requests typically.
Exploit Attack: Exploiting is a crucial way to
gain control of the system. The user finds a
vulnerability from the target system and then
uses it to obtain permission to control the target
system (Burhan et al., 2018).
Finally, the False Terminal Trigger threat often
takes place in the application Layer. An attacker is
able to trigger the maloperation of the terminal by
sending fake messages to the terminal through SMS.
All types of security threats in different layers are
shown in Table 2.
5.1.3 Analysis of “Non-sensitive” Data
Another key point that needs attention is that personal
data can be indirectly generated from "non- sensitive"
information. The data seems to be irrelevant to
personal information, but using big data techniques
for in-depth correlation analysis and mining will
reveal useful information. For example, it is
demonstrated that even in the case of device
encryption, the privacy-sensitive home activity can be
inferred by analyzing the Internet traffic in smart
homes through Internet Service Provider (ISP) or
other network observers (Apthorpe et al., 2017).
Many intelligent devices in smart homes have sensors
always connected to the Internet and for some
devices, and the traffic rate is affected by different
user activities. By drawing the send/receive rates of
the specific equipment's streams, attackers can
observe fluctuations to infer the user activities
(Apthorpe et al., 2017). Taking an example in
Apthorpe's paper (2017), by observing the
send/receive rate of Sense Sleep Monitor, it is
possible to infer the user's working and sleeping time
because it would reach the peak when the user activity
Table 2: Security Threats in Different Layers.
Physical Attack, Eavesdropping, Simulation Attack, Replay Attack,
Timing Attack
DoS Attack, Storage Attack, Exploit Attack, Fake base station attack
Cross-Site Scripting, False Terminal Trigger
Smart Home based on Internet of Things and Ethical Issues
In Zheng’s article (2018), the authors brought
forward the view that not only A/V (audio/video)
devices in the smart home should be paid attention to,
but also the non-A/V devices should be watched out
for the privacy risks. As the concepts of smart home
data are generally divided into two part: "sensitive"
and "non-sensitive”, it is a risk to show no skepticism
about “non- sensitive” data with unaware of the data
analysis capabilities of inferring sensitive
information from “non-sensitive” data.
5.1.4 Improper Information Collection
Whether personal information can be reasonably
collected, used and cleared is also an important issue.
In big data scenarios, the omnipresent data gathering
techniques and numerous varied data processing
techniques pose significant challenges to people's
privacy protection in this area. Data information
collection is basically “automatically” implemented
by computer networks and smart applications in
different smart home devices. As data collection
becomes more convenient and low-cost, the
imperfection of legal regulation leads to the confusion
of the object of data collection. Some data is collected
without the user's knowledge or consent. Another
possibility is that although users agree with the
applications or devices to collect data, they do not
really understand the content and purpose of the
collected data or lack sufficient freedom of choice
(Mantelero, 2017). For example, users have to accept
all the data collection terms if they want to use the
service. If the users want to withdraw their consent, it
is difficult because of the complex data processing
and the unfriendly digital interfaces (Mantelero,
2017). The vast amount of information collected,
coupled with increasingly intelligent analytical tools,
will make big data controllers aware of almost
everything related to individuals in the home, which
is a situation that everyone is not willing to face.
5.1.5 Data Abuse
Personal information abuse is inevitable due to the
pursuit of maximizing the value of data, putting
personal privacy at risk. There is an inevitable
conflict between the appeal of open and shared big
data resources and protecting personal privacy.
Because of the unclear rights and responsibilities of
data collection and use, some public departments and
large companies over-collect, occupy data and
infringe on data information owners' legitimate rights
and interests. When data is collected, how the data
will be used or analyzed is not always known or
expected because of the complexity of data analytics
(Mantelero, 2017). Moreover, owners lose control of
the data after it has been collected. Some people or
companies have the ability to occupy and utilize
substantial data resources in a better way, while it is
hard for others to do the same thing. This forms a data
gap and creates a problem of unfair distribution of
information dividends, which intensifies differences
between groups and social conflicts. Back to the
smart home, on the one hand, service providers need
to analyze daily data generated from smart homes to
improve service quality. On the other hand, over-
analysis of data may reveal privacy that some
residents do not want others to know.
5.2 Other Ethical Issues
Besides security and privacy issues, some other
ethical issues and malicious behavior of enterprises
are among them. For example, for consumers to
continue to use their products, some smart home
enterprises would intentionally create a complex IoT
ecosystem where only their own products can be
applied. In order to adapt to the system, consumers
have to choose the company's products when they
want to add new smart home products. The company
may also sign complicated contracts with users,
making it difficult for them to change to other IoT
systems (Cremer et al., 2016).
As there are various ethical issues in smart homes, it
is vital to understand users' perceptions better. In
Zheng's article (2018), researchers interviewed some
smart homeowners ranging from 23–45 years about
their views on the privacy of smart homes and they
came to some conclusions through analysis. This
paper will briefly summarize some noteworthy
individual perception in Zheng's article. Smart home
users can accept the risk of personal privacy leakage
in exchange for the convenience and connectedness
of smart homes to a certain extent. However, they
hold different views on different entities collecting
and accessing data, such as manufactures, advertisers,
Internet Service Providers and government. Owners
are most concerned about the government and pay the
least attention to manufacturers because they believe
it is necessary and reasonable for manufactures to
improve their devices by accessing their usage data.
Furthermore, smart home users tend to trust big
brands before they thoroughly understand, although
some do not take adequate measures to protect
personal privacy. One of the implied reasons is that
FEMIB 2021 - 3rd International Conference on Finance, Economics, Management and IT Business
individuals are unwilling to spend time and energy,
protecting personal privacy and rationalizing their
behavior by trusting big brands.
As smart home gradually enters more people’s lives,
the ethical issues related to it have raised concerns of
smart home shareholders. For the purpose of
protecting data security and privacy and improve
other ethical problems, many methods can be
proposed in different aspects.
7.1 Data Security
For technology, personal data should be minimized
for privacy protection. The privacy level of collected
data by the smart home environment should be
evaluated and data is supposed to be processed before
implementing the SH system (Lee, 2017). Data
segmentation is one of the conventional methods for
data protection. It refers to the division of logically
unified data into smaller, independently manageable
physical units for storage. By partitioning data,
personal data can be processed and analyzed
separately, reducing privacy leakage risk. Another
advanced method is data aggregation, referring to the
process of selecting, analyzing and categorizing the
relevant data, and finally obtaining the desired results.
For smart homes, the greatest aggregation level and
the least amount of details should apply to personal
data (Lee, 2017). Additionally, differential privacy
technology can be mentioned. Its function is using
cryptographic algorithms to "encrypt" the user's
information to the server. The company can calculate
the user group's behavior patterns through the
"encrypted" data, but cannot resolve the data of the
individual user. This mechanism makes sure that each
individual's data will not be revealed.
Simultaneously, it is still not difficult for the outside
world to understand the general statistical
information of the dataset. (Tsou et al., 2017).
7.2 Manufacturers and Service
For manufacturers of smart home devices and the
service providers, they should also take
responsibility. They must be responsible for
protecting the collected user's personal information
and preventing information leakage, damage, or loss.
Personal data collected by them may not be altered
since it may not be provided to others without the data
owners' consent. The data information collector must
use the obtained data information following the
prescribed or agreed use, and may not be used for
other purposes. Moreover, they should provide more
natural ways for users to handle their private data. For
example, it is suggested that smart home applications
allow users to check and choose the data they want to
be recorded or analyzed, and should also allow them
to delete their data (Zheng et al., 2018).
7.3 Individuals
For smart home occupants, they need to raise their
personal consciousness and use related security
technologies. In the era of big data, it is necessary for
everyone to take the initiative to learn this knowledge
and understand the potential risks that may exist in
this area elated to personal privacy disclosure, so as
to learn the method of protecting their private data
from being leaked. It is very important for the
consumers to pay attention to the issues related to
personal privacy and data security when they
purchase smart home products and carefully check
the privacy policy at the beginning of use as well.
This paper firstly reviews the concept and three-layer
structure of the IoT and introduces the smart home
established on IoT with its benefits and components.
Data analytics in a smart home is mentioned, which
is the core of the smart home and brings many
benefits. A kind of big general data analysis
implementation is discussed for understanding the
data analyzing process in a smart home. Besides the
convenience of smart homes, it also poses challenges
in ethical areas, mainly data security and privacy.
Attack and analysis of “non-sensitive” data can cause
threats to personal information security. Data
collectors may gather information improperly and
abuse private data. Under this situation, the smart
home occupant's perception is summarized, showing
immature ideas in some aspects. Finally, there are
some recommendations made for different objects,
such as users, manufacturers. In conclusion, data
analytics in the smart home makes users live more
convenient and interconnected, but more
considerations should be taken to solve ethical issues.
Smart Home based on Internet of Things and Ethical Issues
This work is supported by VC Research (grant
number VCR 0000095).
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