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standards, large amount of big data exchanges, etc. provide
seamless service integration, improve application interfaces
as well as the user quality of living. Nearly two thirds of the
available devices in smart cities are wireless, which illus-
trates the communication synergies that can be implemented
for diverse applications and at large scale.
Once the system design is established (comprised of
multiple embedded devices serving as autonomous agents),
security and safety are major concerns when managing,
storing, computing, and analyzing user data [
9
,
20
]. Thus,
ICTs must employ smart security schemes ensuring the con-
fidentiality of the data residing in the mentioned devices.
In 2009, the world’s 1st smart city in Santander, Spain had
around 20,000 decentralized sensors ,which were distributed
throughout the urban landscape, collecting and transferring
user information. Initially, during the transformation from
offline processing and analysis to digitization with smart
computerized
processing, analyst and technical people finds
it a bit difficult due to their high-speed processing capabili-
ties and result oriented computations [
4
,
13
]. Later stages
of data processing made them clear that there is no manual
analysis and process re-verification is necessary due to their
encryption-based complex algorithms.
Decades of advancements in ICT have caused serious
impacts on the socio-economic well-being of people living
in smart cities. The rapid growth of the internet and commu-
nications enabled smart city residents to remain connected to
the internet in every aspect of their lives. Thus, IoT became
an inseparable element of every smart community. Many
researchers [
7
,
21
,
22
] surveyed the impact of IoT in smart
city expansion. Focus on urban IoT scenarios with their
application-specific objectives made clear that the transfor-
mation to smart cities requires considerable planning and
technology-driven testing in real time. IoT can be found in
many applications such as traffic systems, healthcare, home
and industrial automation, power generation and delivery
sectors, and in many customized services aimed at assist-
ing certain demographics. An empirical survey on urban
IoT helps identify the intertwined concept of quality and
quantity; improving the quality of the living environment in
urban IoT infrastructure will also
assist the economic growth
of the city [
4
]. During this IoT integration process, the city
operational costs are greatly reduced, while the fundamental
lifestyle of people improves significantly.
A case study performed in Padova shows that open source
data obtained from different sensors and actuators installed
in many public areas can be integrated using IoT and used
for monitoring the entire city from a centralized govern-
ment-operated interface. IoT provides a wide range of design
options and solutions; however, the security of the devices
and the algorithms used should conform to the current
cyber-security standards. The authors in [
21
,
23
,
24
] present
a detailed survey on security issues, challenges, and their
attack mitigation for IoT devices in smart homes. Since data
security is handled by the service providers, data confidenti-
ality,
resource availability, authorization, and integrity must
also be ensured along with non-repudiation. The authors
performed an adversarial analysis, where IoT risk factors
were analyzed and categorized (in three different groups)
based on their severity and economic impacts [
25
]. Domestic
electrification, transportation, and grid integration are the
key areas analyzed in the survey along with potential coun-
termeasures. In such smart IoT setups, enormous amounts
of data are generated from multiple sensor and embedded
devices, thus proper attack categorization and comprehen-
sive security analyses are necessary to ensure data security
[
26
,
27
].
The need for efficient big data management becomes vital
due to the inherent advantages that can provide to users and
enterprises. Big data analysis can offer automatic sugges-
tions and user-friendly choices for consumers, and can also
be employed in various other industries, such as e-com-
merce, transportation, health and medical field, and edu-
cation. The collected data have to be processed and stored
before computations can be executed
and useful results are
generated. Big data privacy protection mechanisms are lev-
eraged to safeguard customer data [
20
] . Encryption tools,
privacy-preserving computation models, complex data man-
agement algorithms are required to preserve the confidential-
ity of user-generated data (stored in government databases)
for further analysis and processing. Networking standards
should also conform to security recommendations and best
practises when handling sensitive user data, promoting trust,
and assisting in building secure connected communities.
In 2015, United States (U.S.) Networking and Information
Technology Research and Development (NITRD) program
released a framework for smart infrastructure communica-
tion zones which includes IoT-BIC and envisioned the devel-
opment of completely autonomous cyber-physical connected
smart community (CPSC) [
3
]. This CPSC would possess
networking units, communication devices, big data stack,
decision-making models, and high-fidelity cloud-assisted
real-time assistance systems. With the complete smart infra-
structure, industries and power distribution
units will also
be easily accessible, while the traffic management systems
would become more eco-friendly. To avoid data congestion
from the embedded agents, all seven distinct components
must be collectively controlled and maintained [
28
].
Services that run in the background and can overcome
potential abnormal conditions should be designed to main-
tain safety and security while complying with the inter-
national standards organization (ISO) regulations [
29
].
Although big data management may endorse the growth
of smart cities the user accessibility to resources in such
ecosystems can become a challenging task. To ensure
user access to the available resources, cloud infrastructure
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must be enabled in these smart communities. This cloud-
assisted data collection, resource management, and appli-
cation processing can help users get their desired results
promptly. From banking and parking payments to other
applications like billings, medical records, driving assis-
tance, etc., data can be stored in the cloud and can be
instantly delivered to the authorized users. These cloud
databases require sophisticated
big data management
schemes and robust IoT connectivity mechanism for seam-
less data communications. During the last few decades,
cloud service providers like Google, Microsoft, and other
e-commerce industries have been utilizing both private
and public cloud infrastructures assisting real-time appli-
cations [
17
,
30
]. The mentioned cloud services requires
substantial internet-connected resources and large data
storage facilities for the collection, processing, and analy-
sis of the aggregated data. As a result, in smart commu-
nities the three essential components, i.e., BIC, must be
leveraged and secured for long-term sustainable economic
growth and user-friendly ecosystems.
