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Learning Python for Forensics

You're reading from   Learning Python for Forensics Leverage the power of Python in forensic investigations

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781789341690
Length 476 pages
Edition 2nd Edition
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Authors (2):
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Preston Miller Preston Miller
Author Profile Icon Preston Miller
Preston Miller
Chapin Bryce Chapin Bryce
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Chapin Bryce
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Table of Contents (15) Chapters Close

Preface 1. Now for Something Completely Different FREE CHAPTER 2. Python Fundamentals 3. Parsing Text Files 4. Working with Serialized Data Structures 5. Databases in Python 6. Extracting Artifacts from Binary Files 7. Fuzzy Hashing 8. The Media Age 9. Uncovering Time 10. Rapidly Triaging Systems 11. Parsing Outlook PST Containers 12. Recovering Transient Database Records 13. Coming Full Circle 14. Other Books You May Enjoy

Creating fuzzy hashes

Now that we've mastered how to generate cryptographic hashes, let's work on generating fuzzy hashes. We'll discuss a few techniques we could employ for similarity analysis, and walk through a basic example of how ssdeep and spamsum employ rolling hashing to help generate more resilient signatures.

It may go without saying that our most accurate approach to similarity analysis is to compare the byte content of two files, side by side, and look for differences. While we may be able to accomplish this using command-line tools or a difference analysis tool (such as kdiff3), this only really works at a small scale. Once we move from comparing two small files to comparing many small files, or a few medium-sized files, we need a more efficient approach. This is where signature generation comes into play.

To generate a signature, we must have a few...

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