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Hands-On Machine Learning for Cybersecurity

You're reading from   Hands-On Machine Learning for Cybersecurity Safeguard your system by making your machines intelligent using the Python ecosystem

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781788992282
Length 318 pages
Edition 1st Edition
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Authors (2):
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Soma Halder Soma Halder
Author Profile Icon Soma Halder
Soma Halder
Sinan Ozdemir Sinan Ozdemir
Author Profile Icon Sinan Ozdemir
Sinan Ozdemir
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Table of Contents (13) Chapters Close

Preface 1. Basics of Machine Learning in Cybersecurity FREE CHAPTER 2. Time Series Analysis and Ensemble Modeling 3. Segregating Legitimate and Lousy URLs 4. Knocking Down CAPTCHAs 5. Using Data Science to Catch Email Fraud and Spam 6. Efficient Network Anomaly Detection Using k-means 7. Decision Tree and Context-Based Malicious Event Detection 8. Catching Impersonators and Hackers Red Handed 9. Changing the Game with TensorFlow 10. Financial Fraud and How Deep Learning Can Mitigate It 11. Case Studies 12. Other Books You May Enjoy

Decision Tree and Context-Based Malicious Event Detection

Malware destructs computer exploits that are responsible for increased CPU usage, slower computer speeds, and much more. It reduces network speeds, freezes or crashes systems, and modifies or deletes files. Malware often messes with default computer configurations and performs strange computer activities with or without the knowledge of a user.

Malicious software is used to steal data, bypass firewalls, and handicap access controls. Malware, at the end of the day, hosts some sort of malicious code and can be categorized into multiple types based on the type of malicious activity it performs.

Next, we will discuss a list of such malware and the injections that it performs:

  • Types of malware
  • Malicious data injection in databases
  • Malicious data injection in wireless networks
  • Intrusion detection with decision tree
  • Malicious...
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