The Silicon Review - Best Business Review Magazine 10 Best Security Companies 2019 | Page 42

a better ability and scalability to
secure different types of data in
different stages.
• Encryption: Firms have to
What Does Securing
Big Data Platforms
Mean in Today’s World?
E
ver since big data has come
into use, the amount of
information managed by
enterprises has skyrocketed. Data
volumes have been constantly
expanding and firms want to
extract value from the data in
order to tap into the opportunities
that it contains. But due to its
centralised nature, it creates new
security challenges. Also, big data
deployments pose as valuable
targets for attackers.
When big data is subjected to
ransomware attacks and data
infiltration, organisations will
have to go through severe losses.
Therefore it is critically essential
to secure big data platforms and in
order to do that, a mix of traditional
and latest security toolsets along
with intelligent processes to
monitor security is needed.
The Challenges and
Pitfalls in Big Data
Security
42
Securing big data throw many
challenges on the path of
organisations. These challenges are
not limited to just on-premise big
data platforms but also pertain to
the cloud. When it comes to hosting
the big data platform in the cloud,
firms shouldn’t take anything for
APRIL 2019
granted; instead they should work
in close association with their
providers and have strong security
service level agreements. Some of
the typical challenges on the way
to securing big data are mentioned
below.
•
•
•
•
•
The relatively new technology
of advanced analytic tools for
big data and non-relational
databases are difficult to protect
with security software and
processes
Data is sometimes mined by big
data administrators without
prior notification or permission.
The size of big data installation
is way too huge for routine
security audits
Though security tools can
protect data ingress and
storage, they still fail to create
the same impact on data output
to multiple locations
When the security processes
are not regularly updated, firms
remain at the risk of data loss
and exposure
Big Data Security
Technologies
Big data security technologies have
been existing since a while, and
there’s nothing new about them.
However, they have evolved to have

depend on encryption tools
to secure data in-transit and
at-rest across massive data
volumes. These tools also need
to be capable of working with
different analytics toolsets and
output data.
• Centralised Key
Management: This is one

of the best practices to ensure
data security. Usually used
in environments with a wide
geographical distribution,
centralised key management
involves on-demand key
delivery, policy-driven
automation, logging, abstracting
key management from key
usage, etc.
• User Access Control: Firms

need to invest in strong user
access control to automate
access based on user and
role-based settings even if the
management overhead gets
high. That’s because practicing
minimal control can lead to
disastrous effects on the big
data platform.
• Intrusion Detection and
Prevention: IPS enables
security admins to protect
the big data platform from
intrusion, and in case the
intrusion attempt succeeds, the
IDS quarantines the intrusion
before and significant damage.

• Physical Security: The

importance of physical
security systems shouldn’t
be ignored. It can control the
access of data by strangers
as well as staff members
who don’t have the authority
to be in sensitive areas.
SR