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Sudheesh Narayanan - Securing Hadoop

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Sudheesh Narayanan Securing Hadoop

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Implement robust end-to-end security for your Hadoop ecosystem

Overview

  • Master the key concepts behind Hadoop security as well as how to secure a Hadoop-based Big Data ecosystem
  • Understand and deploy authentication, authorization, and data encryption in a Hadoop-based Big Data platform
  • Administer the auditing and security event monitoring system

In Detail

Security of Big Data is one of the biggest concerns for enterprises today. How do we protect the sensitive information in a Hadoop ecosystem? How can we integrate Hadoop security with existing enterprise security systems? What are the challenges in securing Hadoop and its ecosystem? These are the questions which need to be answered in order to ensure effective management of Big Data. Hadoop, along with Kerberos, provides security features which enable Big Data management and which keep data secure.

This book is a practitioners guide for securing a Hadoop-based Big Data platform. This book provides you with a step-by-step approach to implementing end-to-end security along with a solid foundation of knowledge of the Hadoop and Kerberos security models.

This practical, hands-on guide looks at the security challenges involved in securing sensitive data in a Hadoop-based Big Data platform and also covers the Security Reference Architecture for securing Big Data. It will take you through the internals of the Hadoop and Kerberos security models and will provide detailed implementation steps for securing Hadoop. You will also learn how the internals of the Hadoop security model are implemented, how to integrate Enterprise Security Systems with Hadoop security, and how you can manage and control user access to a Hadoop ecosystem seamlessly. You will also get acquainted with implementing audit logging and security incident monitoring within a Big Data platform.

What you will learn from this book

  • Understand the challenges of securing Hadoop and Big Data and master the reference architecture for Big Data security
  • Demystify Kerberos and the Hadoop security model
  • Learn the steps to secure a Hadoop platform with Kerberos
  • Integrate Enterprise Security Systems with Hadoop security and build an integrated security model
  • Get detailed insights into securing sensitive data in a Hadoop Big Data platform
  • Implement audit logging and a security event monitoring system for your Big Data platform
  • Discover the various industry tools and vendors that can be used to build a secured Hadoop platform
  • Recognize how the various Hadoop components interact with each other and what protocols and security they implement
  • Design a secure Hadoop infrastructure and implement the various security controls within the enterprise.

Approach

This book is a step-by-step tutorial filled with practical examples which will focus mainly on the key security tools and implementation techniques of Hadoop security.

Who this book is written for

This book is great for Hadoop practitioners (solution architects, Hadoop administrators, developers, and Hadoop project managers) who are looking to get a good grounding in what Kerberos is all about and who wish to learn how to implement end-to-end Hadoop security within an enterprise setup. Its assumed that you will have some basic understanding of Hadoop as well as be familiar with some basic security concepts.

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Securing Hadoop

Securing Hadoop

Copyright 2013 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: November 2013

Production Reference: 1181113

Published by Packt Publishing

Ltd.Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78328-525-9

www.packtpub.com

Cover Image by Ravaji Babu (<>)

Credits

Author

Sudheesh Narayanan

Reviewers

Mark Kerzner

Nitin Pawar

Acquisition Editor

Antony Lowe

Commissioning Editor

Shaon Basu

Technical Editors

Amit Ramadas

Amit Shetty

Project Coordinator

Akash Poojary

Proofreader

Ameesha Green

Indexer

Rekha Nair

Graphics

Sheetal Aute

Ronak Dhruv

Valentina D'silva

Disha Haria

Abhinash Sahu

Production Coordinator

Nilesh R. Mohite

Cover Work

Nilesh R. Mohite

About the Author

Sudheesh Narayanan is a Technology Strategist and Big Data Practitioner with expertise in technology consulting and implementing Big Data solutions. With over 15 years of IT experience in Information Management, Business Intelligence, Big Data & Analytics, and Cloud & J2EE application development, he provided his expertise in architecting, designing, and developing Big Data products, Cloud management platforms, and highly scalable platform services. His expertise in Big Data includes Hadoop and its ecosystem components, NoSQL databases (MongoDB, Cassandra, and HBase), Text Analytics (GATE and OpenNLP), Machine Learning (Mahout, Weka, and R), and Complex Event Processing.

Sudheesh is currently working with Genpact as the Assistant Vice President and Chief Architect Big Data, with focus on driving innovation and building Intellectual Property assets, frameworks, and solutions. Prior to Genpact, he was the co-inventor and Chief Architect of the Infosys BigDataEdge product.

I would like to thank my wife, Smita and son, Aryan for their sacrifices and support during this journey, and my dad, mom, and sister for encouraging me at all times to make a difference by contributing back to the community. This book would not have been possible without their encouragement and constant support.

Special thanks to Rupak and Debika for investing their personal time over weekends to help me experiment with a few ideas on Hadoop security, and for being the bouncing board.

I would like to thank Shwetha, Sivaram, Ajay, Manpreet, and Venky for providing constant feedback and helping me make continuous improvements in my securing Hadoop journey.

Above all, I would like to acknowledge my sincere thanks to my teacher, Prof. N. C. Jain; my leaders and coach Paddy, Vishnu Bhat, Sandeep Bhagat, Jaikrishnan, Anil D'Souza, and KNM Rao for their mentoring and guidance in making me who I am today, so that I could write this book.

About the Reviewers

Mark Kerzner holds degrees in Law, Math, and Computer Science. He has been designing software for many years and Hadoop-based systems since 2008. He is the President of SHMsoft, a provider of Hadoop applications for various verticals, and a co-author of the Hadoop illuminated book/project. He has authored and co-authored books and patents.

I would like to acknowledge the help of my colleagues, in particular, Sujee Maniyam, and last but not the least, my multitalented family.

Nitin Pawar started his career as a Release Engineer and Tools Developer, then moved into different roles such as operations, solutions engineering, process engineering, and Big Data analytics. Currently, he is working as a Big Data System Architect, and trying to solve problems related to customer success management. He has mainly been working with technologies revolving around the first generation Hadoop ecosystem.

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Preface

Today, many organizations are implementing Hadoop in production environments. As organizations embark on the Big Data implementation journey, security of Big Data is one of the major concerns. Securing sensitive data is one of the top priorities for organizations. Enterprise security teams are worried about integrating Hadoop security with enterprise systems. Securing Hadoop provides a detailed implementation and best practices for securing a Hadoop-based Big Data platform. It covers the fundamentals behind Kerberos security and Hadoop security design, and then details the approach for securing Hadoop and its ecosystem components within an enterprise context. The goal of this book is to take an end-to-end enterprise view on Big Data security by looking at the Big Data security reference architecture, and detailing how the various building blocks required by an organization can be put together to establish a secure Big Data platform.

What this book covers

, Hadoop Security Overview , highlights the key challenges and requirements that should be considered for securing any Hadoop-based Big Data platform. We then provide an enterprise view of Big Data security and detail the Big Data security reference architecture.

, Hadoop Security Design

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