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Big Data Forensics: Learning Hadoop Investigations

Big Data Forensics: Learning Hadoop Investigations

By : Joe Sremack
5 (3)
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Big Data Forensics: Learning Hadoop Investigations

Big Data Forensics: Learning Hadoop Investigations

5 (3)
By: Joe Sremack

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)
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9
Index

Running Hadoop

Hadoop can be run from a number of different platforms. Hadoop can be installed and run from a single desktop, from a distributed network of systems, or as a cloud-based service. Investigators should be aware of the differences and versed in the various architectures. Hadoop runs in the same manner on all three setups; however, collecting evidence may require different steps depending on how the data is stored. For instance, a cloud-based Hadoop server may require a different collection because of the lack of physical access to the servers.

This section details how to set up and run Hadoop using a free virtual machine instance (LightHadoop) and a cloud-based service (Amazon Web Services). Both LightHadoop and Amazon Web Services are used in the examples throughout this book. They serve as testbed environments to highlight how Big Data forensics is performed against different setups.

LightHadoop

Many of the examples in this book are intended to be hands-on exercises using LightHadoop...

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