This document outlines the agenda for a presentation on security issues related to big data in cloud computing. The presentation will introduce cloud computing, big data, Hadoop, HDFS, and MapReduce. It will discuss big data applications and advantages. The major focus will be on security issues and challenges with big data in cloud environments. The presentation will propose several approaches to secure cloud environments handling big data, such as file encryption, network encryption, logging, authentication, and access control. It will conclude that securing cloud environments is important for organizations using them for complex operations.

1. Arun Kumar.M
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ISE, VIT

2. Agenda
1. INTRODUCTION
2. MOTIVATION AND RELATED WORK
3. ISSUES AND CHALLENGES
4. THE PROPOSED APPROACHES
5. CONCLUSION
AGENDA
• INTRODUCTION
• CLOUD COMPUTING
• BIG DATA
• HADOOP,HDFS AND MAP REDUCE
• BIG DATA APPLICATIONS AND ADVANTAGES
• ISSUES AND CHALLENGES
• THE PROPOSED APPROACHES
• CONCLUSION
• REFERENCES
AGENDA

3. INTRODUCTION
• The main focus is on security issues in
cloud computing that are associated
with big data.
• In order to analyze complex data it is
very important to securely store,
manage and share large amounts of
complex data.

4. Cloud Computing
• The goal of Cloud Computing is to make use of
increasing computing power to execute millions of
instructions per second.
• Cloud Computing consists of a front end and back
end.
• Applications which use Cloud Computing are Gmail,
Google Calendar, Google Docs and Dropbox etc.
CLOUD COMPUTING

5. BIG DATA
• Big Data is the word used
to describe massive
volumes of structured
and unstructured data.
• Examples of Big Data are
Credit card transactions
with respect to a Bank,
and Facebook.

6. THREE CHARACTERISTICS OF BIG DATA

7. THE OTHER TWO DIMENSIONS WITH
RESPECT TO BIG DATA
Variability Complexity

8. HADOOP
• Hadoop, which is Java-based
programming framework supports the
processing of large sets of data in a
distributed computing environment.
• Hadoop Framework is used by popular
companies like Google, Yahoo, Amazon
and IBM etc.

9. HADOOP DISTRIBUTED FILE SYSTEM
(HDFS)
• It links together file systems on local nodes to
make it into one large file system.
• HDFS is a file system written in Java for the
Hadoop framework.

10. MAP REDUCE
• A MapReduce program is
composed of a Map()
procedure and a Reduce()
procedure
• The MapReduce
framework consists of a
single master JobTracker
and one slave TaskTracker
per cluster-node.

11. BIG DATA APPLICATIONS
Manufacturing and Bioinformatics are the two
major areas of big data applications.

12. BIG DATA ADVANTAGES
• Data analytics
• The software packages provide a rich
set of tools and options to analyze the
threats
• Errors within the organization are known
instantly.

13. NEED OF SECURITY IN BIG DATA
• Many companies are
using the technology to
store data about their
company.
• For making big data
secure, techniques such
as encryption, logging,
honeypot detection must
be necessary.

14. ISSUES AND CHALLENGES
• Data Protection
• Internode Communication
• Administrative Rights for Nodes
• Authentication of Applications and Nodes
• Logging
• Traditional Security Tools

15. THE PROPOSED APPROACHES
• File Encryption
• Network Encryption
• Logging
• Software Format and Node Maintenance
• Nodes Authentication
• Rigorous System Testing of Map Reduce Jobs
• Honeypot Nodes
• Access Control

16. CONCLUSION
The security is an important aspect for organizations
running on these cloud environments.
Using proposed approaches, cloud environments
can be secured for complex business operations.

17. • Venkata Narasimha Inukollu, Sailaja Arsi and
Srinivasa Rao Ravuri Security issues with big data
in cloud computing (IJNSA), Vol.6, No.3, May
2014.
• N, Gonzalez, Miers C, Redigolo F, Carvalho T,
Simplicio M, de Sousa G.T, and Pourzandi M. "A
Quantitative Analysis of Current Security
Concerns and Solutions for Cloud Computing.".
Athens:2011., pp 231 – 238, Nov. 29 2011- Dec. 1
2011.
• Zhao, Yaxiong , and Jie Wu. "Dache: A data aware
caching for big-data applications using the
MapReduce framework." INFOCOM, 2013
Proceedings IEEE, Turin, Apr 14-19, 2013.
• Changqing Ji, Yu Li, Wenming Qiu, Uchechukwu
Awada, Keqiu Li: Big Data Processing in Cloud
Computing Environments, 2012 International
Symposium on Pervasive Systems.
• www.google.com
REFERENCES

18. Presented by Arun Kumar.M