Security of Data and Privacy Concerns in Analytics

This paper discusses the security and privacy concerns in big data analytics, focusing on the protection of information assets and personal data. It explores privacy requirements, security measures, and the impact of IoT and research on data privacy.

Security of data and privacy concerns in analytics
NAME
AFFILIATION
Abstract – As a result of the rapid increase
and widespread of services of the network,
users on online platform and mobile
devices on the internet causing a
significant growth in the amount of data,
nearly each and every industry is putting a
lot of effort in trying to handle the huge
data. This phenomenon has already started
gaining significance. In addition to
problems in storage of big data and
analyzing it using traditional applications,
problems of security and privacy arise in
big data. Due to this, this paper brings out
concerns on big data and depicts views
regarding security and privacy methods in
literature in the view of data,
infrastructure and application. Through
this, a view regarding privacy and security
in big data is offered.
Key words: Security, Privacy, Big Data
I. INTRODUCTION
A string of events has happened in the recent
years which depict the problems that arise
with the management of the privacy of the
data and information in the digital
environment. They include the Cambridge
and the Facebook Analytica. As a result,
including the digital world executives such
us IBM and Apple, more oversight has been
called for on the use of personal data [10].
Even though a lot of people question about
how policymakers and businesses are
prepared regarding the privacy issues of the
consumers online, everyone acknowledges
that we ought to put our focus on the
research that is productive regarding this
topic. Due to this, research regarding the
connection between marketing analytics and
data privacy are especially essential. The
studies indicate that, it is vital to evaluate
digital privacy of data in order to create trust
through business practices that are sound in
data analytics and to enhance activities
involved in marketing [5].
Studies depict that transparent and proper
policies on privacy lead to increase in
perceptions of consumer fairness and justice
that is distributive in addition to building
trust [4].
II. SECURITY AND PRIVACY
CONCERNS.
Security and privacy in terms of big data is
an issue that is very essential.
Security refers to the way of defending
information assets and information by using

processes, technology and training from: -
Disruption, disclosure, unauthorized access,
destruction, inspection and recording.
Privacy refers to the advantage of having
some kind of control over how information
that is personal is gathered as well as how it
is used. It also refers to the ability of a group
or an individual to prevent information
regarding themselves and others from being
accessed by people compared to the people
authorized to do so. A major concern in
privacy issue of the user is the identification
of information that is personal at the time
data if transmitted over the internet platform
[9].
Security vs Privacy Security focuses on
fundamental data protection while Privacy
majorly focuses of the governance and the
use of personal data. Practices such as
policies setting up are put in place to make
sure that personal information of the
consumers is gathered, given to others and
used in the correct ways. Security majors
mainly in data protection against attacks that
are malicious and against misusing of the
data that has been stolen for the selfish gains
[3]. Security is to adequate when it comes to
addressing of privacy.
A. Privacy requirements in big data
Analytics in big data attract a number of
organizations but a number of them chose
not to use the services as a result of lack of
protection tools of privacy and security that
are actually standard. The below sections
evaluate likely strategies that would help in
upgrading platforms of big data with the
assistance of capabilities of privacy
protection. The development strategies and
the foundations of a structure that enables:
i. The privacy policies specification
managing the accessing to stored
data into platforms of big data.
ii. The creation of enforcement
monitors that are productive for the
policies, and
iii. The incorporation of the monitors
that are generated into the analytics
platforms that are the target.
Proposed techniques that are
enforced for the DBMSs that are
traditional seem inadequate for the
context of big data due to the
execution necessities that are strict
that are required in handling large
volumes of data, data heterogeneity
and the speed that the data is
analyzed at.
The large use of big data has come with its
price; the privacy of the users is at risk.

Conformance that is ensured to terms of
privacy and regulations are inhibited in
current analytics of big data and the
practices of mining. Developers ought to be
able to ensure that their applications adapt to
agreements of privacy and that information
that is sensitive is retained as private
irrespective of the variations in the
applications or/and regulations of privacy
[8].
B. Data privacy online
Studies show that among the highly topics
that are debated relating to the digital
privacy of the information include a number
of national laws of privacy and regulations,
the benefits that are social of big data usage
and culturally practices that are acceptable
[5]. For example, even though studies
indicate that nations with tighter regulations
on privacy experience a lesser number of
issues arising from privacy, the greater
control levels lead to lower effectiveness in
terms of effectiveness and other outcomes of
marketing [6].
The research also indicates that, where there
are high conditions controlling the privacy,
consumers barely click on ads that are
personalized [12]. In regard to the notices of
privacy, the studies indicate that, the
consumers are becoming increasingly
frustrated by them and note reading comes
as a privacy concern, perceptions that are
positive regarding their comprehension and
greater trust levels in the text [7].
C. Data privacy in the Internet of
Things
Internet of Things comprises of the
applications that enable consumers to
regularly check the home appliances statuses
from their smartphones, observe their homes
and coordinate their devices. This causes to
the increase in risk sharing the collected
information that is private [1].
In regard with the IoT, privacy is linked to
things that are smart and services that
surround the consumers. It adopts the
control that is individual over the
processing, collection and storage of
individual information and the awareness
and control in regard to the use and
dissemination of the information [13]. From
the information relayed above, the scholars
note that the policies are not linked with the
market advances, as a result of the overload
of information, unclear use of information
and the rate at which exchange of data takes
place [13]. Due to this, it is very likely that
consumers will have little or no knowledge
that their data has been shared or breached.
Consequently, in the analytics world of
marketing, marketers require as much as
data as can to be gathered through the

Internet of Things in order to give the
consumers personalized experiences that is
efficient. With this regard, marketing
research on analytics can have a focus that is
deeper into areas of research such as;
regulations of privacy that are related to IoT
and the way in which the affect how the
consumer use data, new metrics of
marketing and their connection to privacy of
the consumer and the perceptions of the
consumer as well as their attitudes towards
collection of data and its processing in IoT.
D. Data privacy in research
Research carried out in 2017 indicated that,
discoverability and reuse came about as a
result of sharing of only half about the data
relating to research and a smaller share of it
that was shared openly, compared to what
previous debates had indicated regarding
privacy of the data that, the debates usually
come about from issues arising from data
sharing [11]. Studies indicate that,
researchers experience problems such as
constraints in time, lack of know-how
around standards of data, metadata and
expertise of curation, options of repository
and requirements of funder while trying to
archive, publish and share information [11].
In regard with the big data specifics and
analytics of marketing, it would be specially
exciting to discover the ability that a
dissimilar perspective of data mining or the
utilization of a different method could
impact in the dataset analysis and the
finding of information that is new if it were
to be made accessible to others.
Nonetheless, the issues threatening the
privacy and data breaches in practice could
be upsetting the attitudes of the researchers
towards data sharing and increasing their
efforts into comprehending standards of data
and issues of curation [2].
CONCLUSION
In conclusion, a more structured approach is
proposed and a research stream is required
with regard to privacy of the data and its
connection to analytics of marketing, since
the topics contain significant effects for both
marketers and consumers. Both marketer
and consumer attitudes towards behavioral
outcomes and privacy together with the
common policies of regulation which all the
parties involved have the will to reach for
everyone’s gain are among the areas that
could help for digital users
REFERENCES
1. Adams, M. Big data and individual privacy in
the age of the Internet of Things. Technology
Innovation Management Review 2017; 7 (4): 2–
24.
2. Jain, P., Gyanchandani, M. and Khare, N.,
2016. Big data privacy: a technological

perspective and review. Journal of Big Data,
3(1), p.25.
3. Jing Q, et al. Security of the internet of things:
perspectives and challenges. Wirel Netw.
2014;20(8):2481–501.
4. Krishen, Anjala S., Robyn L. Raschke,
Angeline G. Close, and Pushkin Kachroo. A
power-responsibility equilibrium framework for
fairness: Understanding consumers’ implicit
privacy concerns for location-based services.
Journal of Business Research 2017;73: 20–29.
5. Leonard, P. Customer data analytics: Privacy
settings for ‘Big Data’ business. International
Data Privacy Law 2014;4 (1): 53–69.
6. Martin, K.D., and P.E. Murphy. The role of
data privacy in marketing. Journal of the
Academy of Marketing Science 2017; 45:135–
155.
7. Milne, G.R., and M.J. Culnan. Strategies for
reducing online privacy risks: Why consumers
read (or don’t read) online privacy notices.
Journal of Interactive Marketing 2004;18 (3):
15–29.
8. Petrescu, M. and Krishen, A.S. Analyzing the
analytics: data privacy concerns, 2018.
9. Porambage P, et al. The quest for privacy in
the internet of things. IEEE Cloud Comp.
2016;3(2):36–45
10. Reuters. Apple, IBM chiefs call for more
data oversight after Facebook breach.
https://www.reuters.com/article/us-china-forum-
data/apple-ibm-chiefs-call-for-more-data-
oversight-after-facebook-breach-
idUSKBN1H20JU, 2018
11. Stuart, D., G. Baynes, I. Hrynaszkiewicz, K.
Allin, D. Penny, M. Lucraft, and M. Astell.
Practical challenges for researchers in data
sharing. White paper. Springer Nature.
https://doi.org/10.6084/m9.figshare.5975011,
2018.
12. Tucker, C.E. Social networks, personalized
advertising, and privacy controls. Journal of
Marketing Research 2014;51: 546–562.
13. Walker, K.L. Surrendering information
through the looking glass: Transparency, trust,
and protection. Journal of Public Policy and
Marketing 2016;35 (1): 144–158.