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

Security Incident and Event Monitoring in a Hadoop Cluster

A Security Incident and Event Monitoring (SIEM) system is responsible for collecting, monitoring, analyzing, and generating various security alerts for any suspicious activity in the cluster. SIEM systems usually collect the various system logs, network logs, and application logs to identify these security incidents and events. Hadoop itself can be used to perform the analysis and correlation of these security events in a batch mode.

The first step in any SIEM system is to collect the various system logs and identify corresponding events. The following are the events that need to be monitored in a Hadoop cluster to detect any security incidents:

  • User login and authorization events: User login events in a secured Hadoop cluster are generated when the end users or service principals authenticate themselves within the KDC or EIM system. krb5kdc.log for the KDC in the local Hadoop realm will contain the service login events. The central...