Big Data Security and Privacy Risks: Management and Solutions Report

This report focuses on the security and privacy risks associated with big data management, emphasizing the need for robust security measures to prevent legal and ethical issues. It highlights the limitations of traditional security procedures in handling the vast amounts of data in cloud environments. The report discusses the characteristics of big data, including volume, variety, and velocity, and outlines various security and privacy issues, such as those related to infrastructure, non-relational databases, data analytics, access control, and web interfaces. It also explores the impact of these issues, including risks to parallel programming frameworks, data storage, and access control. To address these challenges, the report proposes a comprehensive security framework that encompasses data masking, encryption, network security, and access controls. The framework aims to ensure data integrity, confidentiality, and authorized access, ultimately providing a secure environment for managing big data. Desklib provides access to this and other past papers and solved assignments.

Information Security
2017

Executive summary:
In this paper, we are going to focus on the security and privacy risks associated with the
management of big data and the recommended solution to overcome the scenario of privacy
issues. The advancement in big data management plays a vital role in taking efficient
decision related with the critical region of enterprise by providing instant information. The
security issues associated with the big data should be handled adequately because the
inefficiency of the security procedures will lead to the consequences of legal issues. The
traditional security procedures are not adequate to handle the big data available on the cloud.
The increasing growth of the digital innovation raises the concern of big data security issues.

Contents
Executive summary:..............................................................................................................................1
Introduction:..........................................................................................................................................4
Requirement of security in the management of big data:.......................................................................4
Security and privacy issues:...................................................................................................................5
Impact of the security issues:.................................................................................................................7
Proposed Security framework for managing big data:...........................................................................8
Conclusion:..........................................................................................................................................11
References:..........................................................................................................................................11

Introduction:
Big data is the large volume of data stored on the internet. The organizations are facing
problems in managing the complex data for retrieval. The management of big data is capable
of resolving the issues related with retrieval of information. The advancement in big data
management plays a vital role in taking efficient decision related with the critical region of
enterprise by providing instant information (Sinanc, 2015). The environment of big data can
be characterised by handling data in petabytes, distribution and management of redundant
data for storage, leveraging the processing related with parallel tasks, increasing the
capabilities of data processing, efficient in insertion and retrieval of information, and central
management of data. In this paper we are going to focus on the security and privacy concerns
associated with the management of big data over the network and what are the possible
solutions to handle the big data (Wayne, 2013). The architecture of the big data environment
is characterised with the 5 V’s model which are composed of variety, volume, veracity,
velocity and value. The following diagram shows the characteristics of the big data
environment.
Requirement of security in the management of big data:
The security issues associated with the big data should be handled adequately because the
inefficiency of the security procedures will lead to the consequences of legal issues (Muoro,

2013). The traditional security procedures are not adequate to handle the big data available on
the cloud. The management of security problems associated with the handling of big data
involves the inclusion of encryption policies, detection by using honey pot, and logging
technique. The increase in the volume of data available on the network will results into the
birth of security and privacy challenges associated with the streamlining of the data (Munaye,
2013).
Security and privacy issues:
The following table shows the list of security and privacy issues associated with Big data:
Security and privacy issues Description
Security associated with the big
data infrastructure
Security issues related with the development of
framework for distributed programming
The data stored in the non-relational databases
Parallel programming infrastructure involves the large
amount of data for performing its tasks simultaneously
(Schmitt, 2013). It makes use of map reduction techniques
for handling data. The inclusion of iterative procedures
can create the scenario of privacy and security issues
(Moreno, 2016).
Privacy issues with non-
relational data management
Scalability in using the technology of data analytics and
mining
Security issues associated with the central management of
the data
Access control associated with the data management
The NOSQL databases are weak in security infrastructure
Data storage at central database Storing the data on transactional logs
Auditing of the granular data
Provenance associated with the management of central
data
The use of multi-tiered devices for storing the data can
create the problem of accuracy and exponential increase of
data.
Integrity of data management Validation and filtering of end point data

Monitoring of the security issues associated with the real
time management system
The multiple sources used for collecting the data requires
special attention of security
The checking of validity of the data is the major security
concern (Parms, 2013)
Exposure to the common
security vulnerabilities
No reporting of vulnerabilities associated with the internal
working of the enterprise
Security issues associated with
the web interface
The exploitation of the interface due to scripting of the
cross-site architecture (Neves, 2016).
Forgery associated with the injection of SQL statements
The security concern should be taken under consideration
for monitoring the leakages of the sensitive information.
Security issues associated with
the authorization techniques
The password policy are not followed for the development
of strong password
Security services provided by
the network are inefficient
The attacker can hack the big data from the network due to
the inefficiency of the security services.
Inefficiency in the encryption
policies
The eavesdropping attack get associated with the IoT
devices
Insecurity in the interface used
by the cloud environment
The inefficiency in the authentication protocols can result
into hacking attack
Insecurity in the interface used
by the mobile devices
The inefficiency in the authentication protocols can result
into hacking attack
Inefficiency in the security
configuration
The configuration is of poor quality for controlling the
transfer of data
Physical security is not accurate The planning of the physical infrastructure is not adequate
Monitoring of the real time data
management
The focus should be given on the infrastructure for
efficient working in the real time environment.
The focus should be given on the data analytics and
mining techniques used for providing data in the big data
environment
The implementation of alert management system with
every node is the problematic area with the handling of
big data.

Enforcement of the data centric
procedures
The data visibility associated with the operating system
Encapsulation of the cryptographic techniques
Access control The authorised and authenticated users should be provided
with the accessible gateway of data for using it. The use of
authentication protocol is the major concern of the big
Data management system. The precision of data should be
taken into consideration for enforcing the sharing of data.
Validation and filtering
procedures used for input data at
end points
Validation and filtering of end point data
Monitoring of the security issues associated with the real
time management system
The multiple sources used for collecting the data requires
special attention of security
The checking of validity of the data is the major security
concern
Provenance of data The use of metadata creates the complexity of data
transfer in the big data environment.
Identification of dependencies is the critical scenario for
the management of big data
The confidentiality of the big data application is the
complex and critical region for handling
Impact of the security issues:
The impact of the security issues associated with the big data management is listed below:
 Security associated with the parallel programming distributed frameworks
 Storing of data on the non-relational databases
 Logging procedures used for data storage
 In carrying out the validation and filtering process with the end data management
system
 Monitoring procedures used for real time infrastructure
 Scalability and privacy issues associated with data analytics and mining techniques
 Enforcement of the data centric storage system

 Access control used on managing granular data (Cloud security alliance, 2012)
 Auditing and logging procedures used on granular data
 Provenance of the data management
Proposed Security framework for managing big data:
The security of the big data can be managed with the implementation of the proposed
framework in the working curriculum of the organization used for handling the big data
(Yosepu, 2015). The security infrastructure of the big data depends on five components
which are classified as below:
 Management of the big data associated with the enterprise
 Identification and accessing of the big data on demand of the user
 Procedures used for protecting privacy of data during sharing or data retrieval
 Security procedures used for network handling
 Proposed infrastructure for managing integrity of the big data of the organization
These major divisions are divided into sub modules for handling the big data securely over
the web which can be classified from the diagram below:
Security Infrastructure of the big data

Management of
the big data
associated with
the enterprise
Identification and
accessing of the
big data on
demand of the
user
Procedures used
for protecting
privacy of data
during sharing or
data retrieval
Security
procedures used
for network
handling
Proposed
infrastructure for
managing
integrity of the
big data of the
organization
Classification of
the big data
Discovery of the
available big
data
Tagging of the
big data
Use of
authentication
protocols
Use of
authorization
protocols
Use of data
metering
system
Use of data
management
with server,
database, and
relational table
Masking of the
data
Redaction of the
data
Tokenization of
big data
Levelling off the
field and
encryption
procedures
Transparency in
the disk level
encryption
protocols
Encryption
procedures
used for folder
management
Prevention
procedures
used for
controlling data
loss
Encryption
procedures
used for packet
level at SSL
layer
Use of Jobtacker
at SSL layer
Use of mapper
reducer
technique
Zoning
procedures
used for
providing
network
security
Use of logging
and auditing
procedures
Use of secured
Linux operating
system
Managing the
integrity of file
Monitoring the
tampering of
data
Monitoring the
use of privileged
data

The management of big data security issues depends on restricting unauthorised accessing of
data, accountability, development of the balance between activities and network approach
(Gahi, 2013). The focus should be given on accessing data from the central database to
overcome the possibility of critical attack. The security should be provided to the sensitive
data to achieve the integrity between the associated data. The data redaction is capable of
providing external level data security. The time management techniques should be used for
fetching the data from the central database. The process of tokenization is used for accessing
data services from the network. Fully homo-morphic encryption is the most recommendable
solution for the smooth functioning of big data available on the cloud network. The
decryption procedures are followed at the receiver end to obtain the plain text. The
trustworthy data should be stored on the network. The ethical consideration should be given
preference to store the data over the network (Singh, 2016). The access controls should be
provided for fetching the data in the authorised manner. The restriction should be provided on
accessing the information from the cloud network. The stored data on the network should be
possessed with authorisation techniques to periodically performing the auditing of the
security procedures. The authentication protocols should be used for accessing the
information from the central database. The sensitivity of the information should be kept
confidential with the use of encryption and cryptographic procedures. The communication
procedures should be used for ensuring the sensitivity and integrity of the big data of the
enterprise. The threat intelligence should be used for monitoring the security procedures for
real time system. The granularity of the data can be achieved with the use of attribute based
encryption procedures. The security concern should be taken under consideration for
monitoring the leakages of the sensitive information (Gaddam, 2015). The risk identification
and risks assessment matrix should be prepared to provide strategic and tactical solution to
the organisation to overcome the situation of complexity arises with the management of big
data. The ethical standards and policies should be used to restrict the hacker from carrying
over hacking activities. The data should be stored in the structured manner to enhance the
retrieval of the information on the demand of the user.

Conclusion:
The management of security problems associated with the handling of big data involves the
inclusion of encryption policies, detection by using honey pot, and logging technique. The
increase in the volume of data available on the network will results into the birth of security
and privacy challenges associated with the streamlining of the data. The management of big
data security issues depends on restricting unauthorised accessing of data, accountability,
development of the balance between activities and network approach. The security of the big
data can be managed with the implementation of the proposed framework in the working
curriculum of the organization used for handling the big data.
References:
Cloud security alliance. (2012). Top 10 big data security and privacy challenges. Retrieved
fromhttps://www.isaca.org/Groups/Professional-English/big-data/GroupDocuments/
Big_Data_Top_Ten_v1.pdf
Gaddam, A. (2015). Securing your big data environment. Retrieved from
https://www.blackhat.com/docs/us-15/materials/us-15-Gaddam-Securing-Your-Big-
Data-Environment-wp.pdf
Gahi, Y. (2013). Big data analytics: Security and privacy challenges. Retrieved from
http://ieeexplore.ieee.org/document/7543859/
Moreno, J. (2016). Main issues in big data security. Retrieved from
http://www.google.co.in/url?sa=t&rct=j&q=privacy%20and%20security%20issues
%20associated%20with%20big
%20data&source=web&cd=7&cad=rja&uact=8&ved=0ahUKEwirztOmyrjWAhUDp
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pdf&usg=AFQjCNFHsoHVfDYme1RD4ap8g9yIPe5Eqw
Moura, J. (2013). Security and privacy issues with Big data. Retrieved from
https://arxiv.org/ftp/arxiv/papers/1601/1601.06206.pdf
Munaye, Y. (2016). Big data security issues, challenges and future scope. Retrieved from
http://www.iaeme.com/MasterAdmin/uploadfolder/IJCET_07_04_002-2/IJCET_07_0
4_002-2.pdf