Book Image

Securing Hadoop

By : Sudheesh Narayan
Book Image

Securing Hadoop

By: Sudheesh Narayan

Overview of this book

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 practitioner's 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.
Table of Contents (15 chapters)
Securing Hadoop
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Securing the Hadoop ecosystem with Project Rhino


Project Rhino aimed to provide an integrated end-to-end data security view of the Hadoop ecosystem.

It provides the following key features:

  • Hadoop crypto codec framework and crypto codec implementation to provide block-level encryption support for data stored in Hadoop

  • Key distribution and management support so that MapReduce can decrypt the block and execute the program as required

  • Enhancing the security features of HBase by introducing cell-level authentication for HBase, and providing transparent encryption for HBase tables stored in Hadoop

  • Standardized audit logging framework and log formats for easy audit trail analysis

    Note

    More details on project Rhino are available at https://github.com/intel-hadoop/project-rhino/.