Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Big Data Forensics: Learning Hadoop Investigations
  • Toc
  • feedback
Big Data Forensics: Learning Hadoop Investigations

Big Data Forensics: Learning Hadoop Investigations

By : Joe Sremack
5 (3)
close
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)
close
9
Index

Forensically collecting a cluster system


Collecting Hadoop data requires acquiring data across multiple cluster nodes. Hadoop's cluster design is structured, so data is distributed across multiple nodes. With the potential for node failure, that data is also redundantly stored across nodes. For a forensic investigator, this means data collection involves collecting data from most or all of the nodes.

In traditional forensic investigations, a single machine or server array is acquired. An investigator can pull the hard drive and perform a physical acquisition of the hard drive. The investigator may not be permitted to turn off the server and pull the server's hard drives. However, the investigator can access the server and collect the server data and any data on attached storage devices.

For Hadoop, or any cluster system, this is rarely the case. A Hadoop cluster may have a series of connected nodes, or its nodes could be geographically distributed. Regardless, multiple nodes are connected...

bookmark search playlist font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete