Learning Python for Forensics: Leverage the power of Python in forensic investigations, 2nd Edition

Learning Python for Forensics: Leverage the power of Python in forensic investigations, 2nd EditionReviews
Author: Preston Miller
Pub Date: 2019
ISBN: 978-1789341690
Pages: 476
Language: English
Format: EPUB
Size: 13 Mb

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Design, develop, and deploy innovative forensic solutions using Python
Digital forensics plays an integral role in solving complex cybercrimes and helping organizations make sense of cybersecurity incidents. This second edition of Learning Python for Forensics illustrates how Python can be used to support these digital investigations and permits the examiner to automate the parsing of forensic artifacts to spend more time examining actionable data.
The second edition of Learning Python for Forensics will illustrate how to develop Python scripts using an iterative design. Further, it demonstrates how to leverage the various built-in and community-sourced forensics scripts and libraries available for Python today. This book will help strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials.
By the end of this book, you will build a collection of Python scripts capable of investigating an array of forensic artifacts and master the skills of extracting metadata and parsing complex data structures into actionable reports. Most importantly, you will have developed a foundation upon which to build as you continue to learn Python and enhance your efficacy as an investigator.
What you will learn

  • Learn how to develop Python scripts to solve complex forensic problems
  • Build scripts using an iterative design
  • Design code to accommodate present and future hurdles
  • Leverage built-in and community-sourced libraries
  • Understand the best practices in forensic programming
  • Learn how to transform raw data into customized reports and visualizations
  • Create forensic frameworks to automate analysis of multiple forensic artifacts
  • Conduct effective and efficient investigations through programmatic processing