Security Challenges in IoT and Big Data

The assignment content discusses the challenges and opportunities in ensuring the security of Big Data and Internet of Things (IoT). It highlights the enormous amount of data generated by IoT devices, the need for real-time processing and analysis, and the importance of addressing security concerns. The report emphasizes the need for developers to work with manufacturers to ensure the security of IoT devices, as well as the importance of implementing robust security measures during data collection. It also discusses the challenges of managing and analyzing massive amounts of data, including issues related to data integrity, confidentiality, and availability. Furthermore, it highlights the rapid pace of innovation in Big Data and IoT technologies, which poses new challenges and opportunities for securing these systems.

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Executive Summary
There is a necessity of Big Data emergence in this present world of technology and
science. People are connected to each other by using various modes of communication where
they can share data and information in different types and forms. As the Big Data, Cloud
Computing and IoT (Internet of Things) are growing in a fast pace there has been an increase in
the concern of privacy and security issue of the information and data system. These issues if not
identified and explored properly there will still be a serious concern about the network system of
any organization.

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Table of Contents
Introduction..........................................................................................................................3
1. Overview on Big Data and IoT Security and Privacy Problems.....................................3
2. Security Information and Security Problems...................................................................5
3. Analysis of tackling Security Problems...........................................................................7
4. Recent Security problem related to the chosen topic.......................................................8
Conclusion.........................................................................................................................10
Reference...........................................................................................................................11

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Introduction
Big Data generally refers to the gathering of huge amount of data sets and complex
information. In this current situation the information technology world there we can see an issue
where these technologies are exceeding the existing storage, communicational and computational
capacities of conventional systems [1]. There are various techniques to connect to people or
organization by the use of internet or any other conventional way. The technique and information
that helps in connecting, is incrementing in a huge rate and volume. But this rapid increase is
also creating a concern about the privacy and security issues of the data. Based on the
networking system and hierarchical models the database system has also advanced its area of use
to the relational and objective database system [15]. By the implementation of web sources these
database can also be accessed via data or web management services. Since there is a great
concern about the security and privacy of these network systems, it is important to know the
aspects of theses security concerns.
In this report we are going to review and research about the privacy and security issues in
domain of Big Data and IoT (Internet of Things).
1. Overview on Big Data and IoT Security and Privacy Problems
Big Data is the set of complex and large data that the traditional data processing software
applications lack capability to handle. Big Data is mainly used to increase the storage capability
and increase the processing power [2]. It is more complex and includes challenges like storage,
analysis, data capturing, transfer files, sharing, visualization, querying, updating information and
privacy. Knowledge management in Big Data has three main functionalities Volume, Variety

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and Velocity. Recently two more V’s has been included Values and Variability. There are
several kind of tools in Big Data analysis like NoSQ, MapReduce that includes Hadoop, S3
storage, Servers and Processing. But as the benefits rises there is a constant introduction of new
and vulnerable [3]. Three has been a rise in the security concern in each of these different
domains. There are privacy and security issues of Big Data by the following aspects:
 Transaction logs protecting and information
 Filtration of end-point inputs and validation
 Calculation of Security distributed framework and similar processes
 Protection and securing of data in real time
 Protection the accessibility control methodology, communication and encryption
 Data provenance
 Access control granular
 Security protection for non-rational data stores
Similarly, IoT refers to the communication paradigm that is recently envisioned as one of
the most vital part of everyday life. It is the network of networks which gives value added
service and in which a lot of massive objects, sensor devices and digital devices are connected
through the ICT (Information Communications Technology) infrastructure. The IoT gathers data
and information at anytime and at anyplace, related to anyone and anything, initially
implementing at the path of network and services [4]. There are privacy and security issues of
Internet of things by the following aspects:
 Consumers those uses free online services like social networking, emails,
websites etc. are aware of the fact that consequently they become the part of the

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online service and hence become the data source for the organizational business.
This helps in analyzing of data sources and improves the satisfaction of the
customers. Here is where the conflict comes when these data are sold to third
party for further analysis without the concern of the security and online service
privacy of the customers [14].
 The number of user’s data that are gathered has to be significantly larger from the
past collection gathered. Some of these technologies can gather such sensitive
information of customers by analyzing the daily activities that may range from the
health conditions to financial records.
2. Security Information and Security Problems
There are several security issues regarding Big Data and IoT [5]:
1. Non-relational data store: Let us take an example of NoSQL databases that is
independent from anyone else as a rule need security (which is rather given, kind
of, through middleware).
2. Endpoints: Security arrangements that draw logs from endpoints should approve
the credibility of those endpoints, or the investigation wouldn't do much good.
3. Real-time compliance or security tools: These create a colossal measure of data;
the key is figuring out how to disregard the false positives, so human ability can
be centered on the genuine ruptures [16].
4. Distributed framework: Most enormous information executions really convey
gigantic handling employments crosswise over numerous frameworks for quicker
investigation. Hadoop is a notable example of open source tech associated with

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this, and initially had no security of any kind. Dispersed preparing may mean less
information handled by any one framework, yet it implies significantly more
frameworks where security issues can manifest.
5. Storage: In the architecture of Big Data, there is a general storage where the data
and information are stored on more than one tier. It depends on the need of cost
vs. performance [13]. Let us take an example like the high prioritized data has to
be stored in the flash media. Hence, the lockdown storage refers to the creation of
a tier-conscious strategy.
6. Access controls: There is requirement of critical; importance that may provide a
system in which authenticates or encrypts verifies the user and hence determine
the priority customer.
7. Data mining solution: Most enormous information usage really circulates gigantic
handling occupations crosswise over numerous frameworks for speedier
investigation. Hadoop is an outstanding occurrence of open source tech engaged
with this, and initially had no security of any kind. Disseminated handling may
mean less information prepared by any one framework, yet it implies significantly
more frameworks where security issues can edit up.These are the core of
numerous enormous information conditions; they discover the examples that
propose business systems. For that very reason, it's especially imperative to
guarantee they're secured against not quite recently outer dangers, but rather
insiders who manhandle organize benefits to get touchy data – including yet
another layer of enormous information security issues.

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8. Granular auditing: This determines the attacks occurred that have been missed
and hence make situations that may improve the situation in future. It is a large
amount of data itself that can be enabled and protected by vital security issues in
Big Data identification.
9. Data provenance concerns primarily about Metadata (data about the data): This is
tremendously vital that helps to know from where the data emerges from [12].
The users who are accessible to the data and what the data are used for. These
data are generally analyzed within minimum amount of time and exceptional pace
in which the breaches get activated. Favored clients occupied with this sort of
action must be altogether checked and nearly observed to guarantee they don't
turn into their own enormous information security issues.
3. Analysis of tackling Security Problems
There is requirement of approximation in this real world since the analyzing and data
collection tools have security aspect that has been functionally stored in the technology. The
deployment of Security and Information Event Management (SIEM) solution is vital to
aggregated logs in security system and the automatic identification of potential breaches. Hadoop
is another simple way to identify the big data security and privacy issues [6]. Thus, Hadoop has
become one of the most popularly used technologies to address breaches. There has been a range
of security leading solutions that has been provided to evolve the technologies which are ideally
commercial grade that to help the lock down process. These systems are generally added
together by the open source contributors, for example Apache Accumulo. Therefore, by the
introduction of Hadoop in Big Data security system, the remaining techniques that can be used
are the authentication check and encryption [7].

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The tacking of data security and privacy challenge in IoT has some unique techniques:
 At first there is requirement of understanding the uniqueness of the challenges
over the security system in IoT and hence making the development of the next
technology accordingly.
 Finding out the risks related to Big Data, greater the amount of sensitive data,
creates greater risk of information system and theft of identity manipulation of
devices, IP theft and manipulation of networks or servers and many more.
 IoT enabling security of data like protection of integrity, confidentiality and
authentication data [8].
 Privacy issues exploration depends on the extent the customer need the privacy
and the techniques by which these issues can be maintained by still making the
data useful for the customers.
 The role of shared trust and metadata assumptions over the end to end security
across platforms.
4. Recent Security problem related to the chosen topic
IoT is a system comprising of physical gadgets, which are additionally embedded with
sensors, hardware, and programming, in this way enabling these gadgets to trade information [9].
This at last permits better joining between genuine physical substances and PC worked
frameworks. IoT is the following huge thing affecting our lives in significant ways and number
of elements. Innovations like Column-arranged databases, SQL in Hadoop, Hive, Wibidata,
PLATFORA, SkyTree, Storage Technologies, Schema-less databases, or NoSQL databases,
Streaming Big Data investigation, Big Information Lambda Architecture, Map-lessen, PIG, and

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so on., helps in managing the huge measure of information created by IoT and different sources.
Real difficulties that can bring ground breaking prizes when they are fathomed:
 Tremendous information volumes[10]
 Trouble in information accumulation
 Contradictory measures
 New security dangers
 No unwavering quality in the information
 Central moves in plans of action
 Gigantic measure of information to break down
 A quickly advancing protection scene
The above focuses are a portion of the difficulties that IoT huge information faces. The
rate in information development in extending each second, stockpiling in a major test, handling
and keeping up is significantly more repetitive [11]. The apparatuses that are created to deal with
the two innovations are step by step changing as per the requirement.

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Conclusion
Associations must guarantee that every enormous datum bases are resistant to security
dangers and vulnerabilities. Amid information accumulation, all the fundamental security
insurances, for example, ongoing administration ought to be satisfied. There is a requirement to
work together on advancing the standards and practice to identify the threats and security issues
regarding Big Data and Internet of things. Since IoT has the requirement of being developed
from level for safety, thus has to be tested. There are a couple of territories of concern and
security and protection and information gathering productivity are likely the most troublesome
issues we are confronting. Remembering the enormous size of huge information, associations
ought to recollect the way that overseeing such information could be troublesome and requires
remarkable endeavors. Be that as it may, making every one of these strides would help keep up
purchaser security. There is a need of developers to work along with the manufacturers to ensure
the security at highest priority. So protecting the customers and organization has to be the
primary concern not the second thought. This report is a survey about the IoT and Big
information security system, the effects of IoT on enormous information, the huge information
advances and the challenges. Since there is a noteworthy effect of IoT on enormous information
we have to rapidly collected, total structure to deal with the day by day evolving conditions.
Security bargain and wasteful aspects in information gathering instruments result in lost status,
cash, time and exertion. Yet, there is trust in light of the fact that both the IoT and the enormous
information are at a developing stage and there will be redesign.

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Reference
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