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
About the Author
About the Reviewers

Integrating Enterprise Identity Management systems

Typically, organizations have a central user identity management system known as Enterprise Identity Management (EIM) system using products such as IBM Tivoli Identity Manager, Oracle Identity Manager, and Windows Active Directory. Enterprise user's access privileges are centrally managed in these systems. These systems manage the user credentials and their roles using groups. User authorization is managed using these security groups. Users are assigned to groups, where each group has a specific authorization and access privilege defined. The user inherits group privileges based on their group membership.

By default, Hadoop uses the logged in Operating System (OS) users and the corresponding user groups to provide the authorization within Hadoop. Hadoop daemons (NameNode, DataNode, and so on) and ecosystem components such as Oozie, Hive, HBase uses these group memberships to determine the level of authorization allowed for the user. By default...