Security of Data and Privacy Concerns in Analytics

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.