Identifying and fully collecting relevant evidence in the early stages of an investigation is critical to success. Improperly collecting evidence will, at a minimum, result in an embarrassing and difficult process of corrective efforts as well as wasted time. At worst, an improper collection will result in working with the incorrect set of data. In the latter case, court sanctions, lost cases, and ruined reputations can be expected. This chapter provides the guidance to ensure all relevant data is identified, so these situations do not occur.
Big Data Forensics: Learning Hadoop Investigations
Big Data Forensics: Learning Hadoop Investigations
Overview of this book
Table of Contents (15 chapters)
Big Data Forensics – Learning Hadoop Investigations
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Starting Out with Forensic Investigations and Big Data
Understanding Hadoop Internals and Architecture
Identifying Big Data Evidence
Collecting Hadoop Distributed File System Data
Collecting Hadoop Application Data
Performing Hadoop Distributed File System Analysis
Analyzing Hadoop Application Data
Presenting Forensic Findings
Index
Customer Reviews