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

Hadoop Kerberos security implementation

Enforcing security within a distributed system such as Hadoop is complex. The detailed requirements for securing Hadoop were identified by Owen O'Malley and others as part of the Hadoop security design. The detailed document is attached with the ticket HADOOP-4487 at A summary of these requirements is explained in this section.

User-level access controls

A brief on the user-level access controls is:

  • Users of Hadoop should only be able to access data that is authorized for them

  • Only authenticated users should be able to submit jobs to the Hadoop cluster

  • Users should be able to view, modify, and kill only their own jobs

  • Only authenticated services should be able to register themselves as DataNodes or TaskTracker

  • Data block access within DataNode needs to be secured, and only authenticated users should be able to access the data stored in the Hadoop cluster

Service-level access controls

Here's a gist of the service...