| Description |
1 online resource : illustrations. |
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text file |
| Series |
Community experience distilled
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Community experience distilled.
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| Note |
Includes index. |
| Contents |
Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Starting Out with Forensic Investigations and Big Data; Computer forensics overview; The forensic process; Identification; Collection; Analysis; Presentation; Other investigation considerations; Equipment; Evidence management; Investigator training and certification; The post-investigation process; What is Big Data?; The four Vs of Big Data; Big Data architecture and concepts; Big Data forensics; Metadata preservation; Collection methods; Collection verification; Summary. |
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Chapter 2: Understanding Hadoop Internals and ArchitectureThe Hadoop architecture; The components of Hadoop; The Hadoop Distributed File System; The Hadoop configuration files; Hadoop daemons; Hadoop data analysis tools; Hive; HBase; Pig; Managing files in Hadoop; File permissions; Trash; Log files; File compression and splitting; Hadoop SequenceFile; The Hadoop archive files; Data serialization; Packaged jobs and JAR files; The Hadoop forensic evidence ecosystem; Running Hadoop; LightHadoop; Amazon Web Services; Loading Hadoop data; Importing sample data for testing; Summary. |
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Chapter 3: Identifying Big Data EvidenceIdentifying evidence; Locating sources of data; Compiling data requirements; Reviewing the system architecture; Interviewing staff and reviewing the documentation; Assessing data viability; Identify data sources in noncooperative situations; Data collection requirements; Data source identification; Structured and unstructured data; Data collection types; In-house or third-party collection; An investigator-led collection; The chain of custody documentation; Summary; Chapter 4: Collecting Hadoop File System Data; Forensically collecting a cluster system. |
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Physical versus remote collectionsHDFS collections through the host operating system; Imaging the host operating system; Imaging a mounted HDFS partition; Targeted collection from a Hadoop client; The Hadoop shell command collection; Collecting HDFS files; HDFS targeted data collection; Hadoop Offline Image and Edits Viewers; Collection via Sqoop; Other HDFS collection approaches; Summary; Chapter 5: Collecting Hadoop Application Data; Application collection approaches; Backups; Query extractions; Script extractions; Software extractions; Validating application collections. |
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Collecting Hive evidenceLoading Hive data; Identifying Hive evidence; Hive backup collection; Hive query collection; Hive query control totals; Hive metadata and log collection; The Hive script collection; Collecting HBase evidence; Loading HBase data; Identifying HBase evidence; The HBase backup collection; The HBase query collection; HBase collection via scripts; HBase control totals; HBase metadata and log collection; Collecting other Hadoop application data and non-Hadoop data; Summary; Chapter 6: Performing Hadoop File System Analysis; The forensic analysis process. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Apache Hadoop.
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Apache Hadoop. |
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Big data.
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Big data. |
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Forensic sciences.
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Forensic sciences. |
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Data mining.
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Data mining. |
| Genre/Form |
Electronic books.
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| Added Title |
Perform forensic investigations on Hadoop clusters with cutting-edge tools and techniques |
| Other Form: |
Print version: Sremack, Joe. Big Data Forensics - Learning Hadoop Investigations. Olton Birmingham : Packt Publishing Ltd, ©2015 9781785288104 |
| ISBN |
9781785281211 (electronic book) |
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1785281216 (electronic book) |
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1785288105 |
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9781785288104 |
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9781785288104 |
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