Big Data Forensics Learning Hadoop Investigations
Book Details:
Publisher: | Packt Publishing |
Series: |
Packt , Learning
|
Author: | Joe Sremack |
Edition: | 1 |
ISBN-10: | 1785288105 |
ISBN-13: | 9781785288104 |
Pages: | 264 |
Published: | Aug 24 2015 |
Posted: | Mar 25 2016 |
Language: | English |
Book format: | PDF |
Book size: | 3.23 MB |
Book Description:
Perform forensic investigations on Hadoop clusters with cutting-edge tools and techniques About This Book * Identify, collect, and analyze Hadoop evidence forensically * Learn about Hadoop's internals and Big Data file storage concepts * A step-by-step guide to help you perform forensic analysis using freely available tools Who This Book Is For This book is meant for statisticians and forensic analysts with basic knowledge of digital forensics. They do not need to know Big Data Forensics. If you are an IT professional, law enforcement professional, legal professional, or a student interested in Big Data and forensics, this book is the perfect hands-on guide for learning how to conduct Hadoop forensic investigations. Each topic and step in the forensic process is described in accessible language. What You Will Learn * Understand Hadoop internals and file storage * Collect and analyze Hadoop forensic evidence * Perform complex forensic analysis for fraud and other investigations * Use state-of-the-art forensic tools * Conduct interviews to identify Hadoop evidence * Create compelling presentations of your forensic findings * Understand how Big Data clusters operate * Apply advanced forensic techniques in an investigation, including file carving, statistical analysis, and more In Detail 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. Style and approach This book is a complete guide that follows every step of the forensic analysis process in detail. You will be guided through each key topic and step necessary to perform an investigation. Hands-on exercises are presented throughout the book, and technical reference guides and sample documents are included for real-world use.
Modern Data Management Principles for Hadoop, NoSQL & Big Data Analytics
Data is the new Gold and Analytics is the machinery to mine, mold and mint it. Data analytics has become core to business and decision making. The rapid increase in data volume, velocity and variety, known as big data, offers both opportunities and challenges. While open source solutions to store big data, like Hadoop and NoSQL offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Organizations that are launching big data initiatives face significant challenges for managing this data effectively. In this book, the author has collected best practices from the world's leading organizations who have successfully implemented big data platforms. He offers the latest tec...
Set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics Overview Write Hadoop MapReduce within R Learn data analytics with R and the Hadoop platform Handle HDFS data within R Understand Hadoop streaming with R Encode and enrich datasets into R In Detail Big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations, and other useful information. Such information can provide competitive advantages over rival organizations and result in business benefits, such as more effective marketing and increased revenue. New methods of working with big data, such as Hadoop and MapReduce, offer alternatives to traditional data warehousing....
Learn exciting new ways to build efficient, high performance enterprise search repositories for Big Data using Hadoop and Solr Overview Understand the different approaches of making Solr work on Big Data as well as the benefits and drawbacks Learn from interesting, real-life use cases for Big Data search along with sample code Work with the Distributed Enterprise Search without prior knowledge of Hadoop and Solr In Detail As data grows exponentially day-by-day, extracting information becomes a tedious activity in itself. Technologies like Hadoop are trying to address some of the concerns, while Solr provides high-speed faceted search. Bringing these two technologies together is helping organizations resolve the problem of information extraction fro...
2007 - 2021 © eBooks-IT.org