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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

The forensic analysis process


Forensic analysis is a process. Investigations are rarely solved in a linear manner. Typically, an investigation begins with a hypothesis that is tested against the data. During the analysis, additional clues or details are uncovered that change or add to the original hypothesis. The process continues iteratively until the investigator can determine exactly what occurred and can provide supporting evidence from the data. This iterative process applies to both traditional computer forensics and Big Data forensics. The following diagram illustrates the steps of the analysis phase:

Figure 1: The analysis process

The starting point of the analysis phase is the investigation hypothesis. The hypothesis is based on the facts of the case and is often developed well in advance of the analysis phase. One example of a hypothesis is, "Former employee X stole trade secrets from Company Y, and then implemented a solution based on those trade secrets for his new employer, Company...

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