Book Image

Big Data Forensics: Learning Hadoop Investigations

Book Image

Big Data Forensics: Learning Hadoop Investigations

Overview of this book

Big Data forensics is an important type of digital investigation that involves the identification, collection, and analysis of large-scale Big Data systems. Hadoop is one of the most popular Big Data solutions, and forensically investigating a Hadoop cluster requires specialized tools and techniques. With the explosion of Big Data, forensic investigators need to be prepared to analyze the petabytes of data stored in Hadoop clusters. Understanding Hadoop’s operational structure and performing forensic analysis with court-accepted tools and best practices will help you conduct a successful investigation. Discover how to perform a complete forensic investigation of large-scale Hadoop clusters using the same tools and techniques employed by forensic experts. This book begins by taking you through the process of forensic investigation and the pitfalls to avoid. It will walk you through Hadoop's internals and architecture, and you will discover what types of information Hadoop stores and how to access that data. You will learn to identify Big Data evidence using techniques to survey a live system and interview witnesses. After setting up your own Hadoop system, you will collect evidence using techniques such as forensic imaging and application-based extractions. You will analyze Hadoop evidence using advanced tools and techniques to uncover events and statistical information. Finally, data visualization and evidence presentation techniques are covered to help you properly communicate your findings to any audience.
Table of Contents (10 chapters)
9
Index

The Hadoop architecture


Hadoop is a reliable system for shared storage and analysis with a rich ecosystem of layered solutions and tools for Big Data. Hadoop is built on the concepts of distribution for storage and computing. It is a cross-platform, Java-based solution. Hadoop can run on a wide array of different operating systems, such as Linux and Windows, because it is built in Java, a platform-neutral language. Hadoop itself is a layer that sits on top of the host operating system. Hadoop's core functionalities are also built in Java and can be run as separate processes. With its own filesystem and set of core functionalities, Hadoop serves as its own abstract platform layer; it can be accessed and run almost entirely independent of the host operating system.

The following figure shows a high-level representation of the Hadoop layers:

Figure 1: The Hadoop architecture layers

The Hadoop layers are an abstraction for how the various components are organized and the relationship between the...