Book Image

Learning Python for Forensics

By : Chapin Bryce
Book Image

Learning Python for Forensics

By: Chapin Bryce

Overview of this book

This book will illustrate how and why you should learn Python to strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. The tutorials use an interactive design, giving you experience of the development process so you gain a better understanding of what it means to be a forensic developer. Each chapter walks you through a forensic artifact and one or more methods to analyze the evidence. It also provides reasons why one method may be advantageous over another. We cover common digital forensics and incident response scenarios, with scripts that can be used to tackle case work in the field. Using built-in and community-sourced libraries, you will improve your problem solving skills with the addition of the Python scripting language. In addition, we provide resources for further exploration of each script so you can understand what further purposes Python can serve. With this knowledge, you can rapidly develop and deploy solutions to identify critical information and fine-tune your skill set as an examiner.
Table of Contents (24 chapters)
Learning Python for Forensics
Credits
About the Authors
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
Index

An overview of databases


Databases provide efficient means of storing large amounts of data in a structured manner. There are many types of databases, commonly broken into two categories: SQL or NoSQL. SQL stands for Structured Query Language and is designed to be a simple language that allows users to manipulate large datasets stored in a database. This includes common databases, such as MySQL, SQLite, and PostgreSQL. NoSQL databases are also useful and generally use JSON or XML to store data, both of which were discussed as common serialized data types in Chapter 4, Working with Serialized Data Structures.