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Mastering Machine Learning for Penetration Testing

You're reading from Mastering Machine Learning for Penetration Testing

Product type Book

Published in Jun 2018

Publisher Packt

ISBN-13 9781788997409

Pages 276 pages

Edition 1st Edition

Languages

Concepts

Penetration Testing

Author (1):

Chiheb Chebbi

Table of Contents (13) Chapters

Preface

1. Introduction to Machine Learning in Pentesting

2. Phishing Domain Detection

3. Malware Detection with API Calls and PE Headers

4. Malware Detection with Deep Learning

5. Botnet Detection with Machine Learning

6. Machine Learning in Anomaly Detection Systems

7. Detecting Advanced Persistent Threats

8. Evading Intrusion Detection Systems

9. Bypassing Machine Learning Malware Detectors

10. Best Practices for Machine Learning and Feature Engineering

11. Assessments

12. Other Books You May Enjoy

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NLP in-depth overview

NLP is the art of analyzing and understanding human languages by machines. According to many studies, more than 75% of the used data is unstructured. Unstructured data does not have a predefined data model or not organized in a predefined manner. Emails, tweets, daily messages and even our recorded speeches are forms of unstructured data. NLP is a way for machines to analyze, understand, and derive meaning from natural language. NLP is widely used in many fields and applications, such as:

Real-time translation
Automatic summarization
Sentiment analysis
Speech recognition
Build chatbots

Generally, there are two different components of NLP:

Natural Language Understanding (NLU): This refers to mapping input into a useful representation.
Natural Language Generation (NLG): This refers to transforming internal representations into useful representations. In...

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Authors (1)

Chiheb Chebbi

Chiheb Chebbi is an InfoSec enthusiast who has experience in various aspects of information security, focusing on the investigation of advanced cyber attacks and researching cyber espionage and APT attacks. Chiheb is currently pursuing an engineering degree in computer science at TEK-UP university in Tunisia. His core interests are infrastructure penetration testing, deep learning, and malware analysis. In 2016, he was included in the Alibaba Security Research Center Hall Of Fame. His talk proposals were accepted by DeepSec 2017, Blackhat Europe 2016, and many world-class information security conferences.

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