You're reading from Digital Forensics with Kali Linux Perform data acquisition, data recovery, network forensics, and malware analysis with Kali Linux 2019.x

Product type Paperback

Published in Apr 2020

Publisher Packt

ISBN-13 9781838640804

Length 334 pages

Edition 2nd Edition

Tools

Kali Linux

Concepts

Forensics

Author (1):

Shiva V. N. Parasram

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Table of Contents (17) Chapters

Preface

1. Section 1: Kali Linux – Not Just for Penetration Testing

2. Chapter 1: Introduction to Digital Forensics FREE CHAPTER

3. Chapter 2: Installing Kali Linux

4. Section 2: Forensic Fundamentals and Best Practices

5. Chapter 3: Understanding Filesystems and Storage Media

6. Chapter 4: Incident Response and Data Acquisition

7. Section 3: Forensic Tools in Kali Linux

8. Chapter 5: Evidence Acquisition and Preservation with dc3dd and Guymager

9. Chapter 6: File Recovery and Data Carving with foremost, Scalpel, and bulk_extractor

10. Chapter 7: Memory Forensics with Volatility

11. Chapter 8: Artifact Analysis

12. Section 4: Automated Digital Forensic Suites

13. Chapter 9: Autopsy

14. Chapter 10: Analysis with Xplico

15. Chapter 11: Network Analysis

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Data imaging and hashing

Imaging refers to the exact copying of data either as a file, folder, partition, or entire storage media or drive. When doing a regular copy of files and folders, not all files may be copied due to their attributes being set to the system or even hidden. To prevent files from being left out, we perform a special type of copy where every bit is copied or imaged exactly as it is on the current medium as if taking a picture or snapshot of the data.

Creating a copy of each bit of data exactly is referred to as creating a physical image. Performing a bit-stream copy ensures the integrity of the copy. To further prove this, a hash of the original evidence and the physical image are calculated and compared. A hash can be compared to a digital fingerprint of the data whereby an algorithm such as MD5, SHA1, SHA-256, or even SHA-512 can be run against the evidence data to produce a unique output. If one bit changes in the evidence and the hash is again calculated...