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Machine Learning for Cybersecurity Cookbook

You're reading from   Machine Learning for Cybersecurity Cookbook Over 80 recipes on how to implement machine learning algorithms for building security systems using Python

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781789614671
Length 346 pages
Edition 1st Edition
Languages
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Author (1):
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Emmanuel Tsukerman Emmanuel Tsukerman
Author Profile Icon Emmanuel Tsukerman
Emmanuel Tsukerman
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Table of Contents (11) Chapters Close

Preface 1. Machine Learning for Cybersecurity 2. Machine Learning-Based Malware Detection FREE CHAPTER 3. Advanced Malware Detection 4. Machine Learning for Social Engineering 5. Penetration Testing Using Machine Learning 6. Automatic Intrusion Detection 7. Securing and Attacking Data with Machine Learning 8. Secure and Private AI 9. Other Books You May Enjoy Appendix

Voice impersonation

Using the new technology of voice style transfer via neural networks, it is becoming easier and easier to convincingly impersonate a target's voice. In this section, we show you how to use deep learning to have a recording of a target saying whatever you want them to say, for example, to have a target's voice used for social engineering purposes or, a more playful example, using Obama's voice to sing Beyoncé songs. We selected the architecture in mazzzystar/randomCNN-voice-transfer that allows for fast results with high quality. In particular, there is no need to pre-train the model on a large dataset of recorded audio.

In the accompanying code for this book, you will find two versions of the voice transfer neural network code, one for GPU and one for CPU. We describe here the one for CPU, though the one for GPU is very similar...

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