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This paper proposes the
threat that lies over the huge piles of data registered, stored by numerous
Enterprise. Each Enterprise big or small, generates a huge stack of data which
can be in regards to data subject to customer’s personal information or it can
be some crucial information regarding the profits and losses of an Enterprise
or in fact regarding some information on company’s private and top secret
policies etc. This data is very crucial to any Enterprise and can decide the
future of a company to rise or demolish at one’s. Hence, this data needs to be
preserved and needs to be protected from getting captured by anyone who could
misuse it.

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These days cloud storage
is widely popular as it reduces the junk in system and makes the data available
to various system without occupying space in any. But, this data stored in
cloud face numerous cyberattack in order to capture them and drain the crucial
information out of it. Hence our paper focuses on this side of the data, it’s
security, the threats it face and the measures to keep it safe.


75% of incidents recorded in the financial services sector came from web
application attacks, distributed denial of service (DDoS) and card skimming;
while cyber espionage and DDoS were particularly common in the manufacturing


Big Data and its sensitivity to attacks:

An enterprise, including your telephone service provider to Google a
famous search engine keeps track of your searching habits to App merchants that
can access some sensitive and personal data of yours via their application/user
agreement license. The more they get in close to end-user’s personal data the
more they hold the personal information of their customer’s/users. This
personal information can tell a person a lot about the user and can be a root
cause to compromise with security and privacy of that user, and some hackers
look for this information in order to plant a malware for that user. So, this
is possible only if they can sneak in a user’s internet usage habits which is
possible if they can hack this data and get the info about numerous users.
Hence, big data looks like a big stack of honey to this greedy bee sort hackers
and hence is more often to experience a cyberattack. Now, in order to prevent
the interest of their fellow users it is the responsibility of these data
holders to keep this



personal information secure and as confidential as possible.

Reasons for these attacks to happen :

User – This can refer to end user authentication and security, it can trace the
data such as users working choice ,user’s taste preferences, his/her location
information as well as the types of browsing trend they have inhabited. They
most widely keep a track as to what site’s are mostly visited by the user and
if any of the can be made prone to a cyber attack or of any of them that makes
it easier for them to attack.

Content – The content present in the data also decides it’s vulnerability to
attack. The type of file/document, password. Patterns suck as (11 characters
together can be an account no, 4 digit together can be an ATM pin). The
attacker could run an algorithm that checks the device repeatedly, basically to
check the information, data patterns they are looking for. These algorithm can
crash the security measures easily as to what they are doing is simply checking
the file type which is not a possible ransomware.

Customers – This would be more crucial fro he customers of a debit
card or a credit card company as well as any company that could involve process
of premium payments. The attackers would not just attack the database of an
ice-cream parlour to get the database of ice-cream prices. They would continue to
look for some database that helps them to gain privacy of people for which they
can demand something in return. Hence, databases of banks and above mentioned companies
get more prone to attacks and therefore would need special attention for information

Networks – They type of network including minute details of it together can play
a crucial role in determining the attack. The Source and Destination as well as
the Time Zone (Date as well as Time), the bandwidth of the network and the
activity. This can be briefly summed up as, that a database of a bank in some
African country is more prone to attacks than compared to that of any Canadian
bank. Reason behind being, that the security and network strength varies.

Device – Together including the software and types constitute of it. Whether
the software is updated on regular basis or not and if the security
certificates are revised on regular basis or not determine the same. If a
device uses an outdated software then, surely it gets more prone to attacks, as
the attacker might have software times more advanced and times more faster than
the device.


Easy tricks to identify this attack:

Irregular trends in transaction – If a system or network makes too many
request for a transaction like it had never made before, can be a determining
factor in a security measure. As, it is possible that this request is a part of
an attack made on the database.

Anonymous IP Addresses making request to
network – If an IP Address of
a request is found to be unusual or hidden, there is a higher possibility that
it’s an attack and the Sender is too smart and knows that IP Address can get
him behind the bars and therefore this can make an attack from a non-detectable
source, PC.

Unusual traffic in the network, can also cause
congestion – When there are
suddenly too many request on a particular, though it can be a normal scenario.
But. There are fair chances that it’s an attack and has been planted to jam the
site/ overload the server to make it inactive to prevent against the attack.

Suspicious software making transaction request – Sometimes the software/ technology can also
help us to detect an attack. What if we are receiving a request via a system
software, never interacted with. Can it be someone’s innovation to ease his
attack on our data base.

Protecting Big Data:

In the year 2017, on July 26 an attack over the database of Arkansas
Oral Center took place also specialising in facial surgery where it made the
X-ray files as well as the documents along the emails became encrypted. Though
the database of the patients was safe and could not be encrypted by the
attacker. The attack was though soon prevented but, it was figured out that due
to this the hospitals and patients had to bear the chaos for almost up to 3

Though the attack here was cured and the losses here couldn’t be
accounted as too big. But, what if the attack was made on a bank and what if it’s
database was encrypted, hacked by the hacker. It could have easily resulted in
losses of precious and confidential customer data including ATM pin, Card No, Account
no etc. That can even sum up to losses of millions of dollars together. Hence,
here comes in picture the concept of Big Data and it’s security.

What makes Big Data more prone to attacks is:

Complexity – Big data knowingly is too complex as it holds huge piles
of information about the customer, Some of them are so informative that if this
information falls in the hands of a wrong person that it’s just like that
person can use that information and cause huge losses to the person information
belongs to.

Huge Pile of data –  When
we call it a Big Data it means that we are talking about the data of a lots and
lots of people. Just imagine, hacking email id of a person to get his personal
info and hacking a bank’s server to get the data of almost 0.1 million
customers. Of course, the second one is more beneficial for the hacker which
means big data gets more prone to such attacks.

Storage – Data so big can’t just fit into any system or any other electronic
device hence they need to be stored on cloud storage/servers. Secondary reason
behind is that such databases needs to be accessible globally as numerous
systems might have rights as well as needs to access that data. Hence the data
is stored on clouds. The only thing preventing such data could be
authentication key which if fooled via complex hacking algorithms can lead to
disasters of leaking information and making it public

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