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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
Author (1):
Chiheb Chebbi Chiheb Chebbi
Profile icon Chiheb Chebbi
Toc

Table of Contents (13) Chapters close

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

Threat-hunting methodology

Threat hunting is an approach for search out, identifying, and understanding APTs. Threat hunting, like any methodological information security mission, is not about tools and utilities. It is a combination of processes, people, and technology.

Threat hunting involves the following steps:

  • Creating hypotheses
  • Investigating by using tools and techniques
  • Uncovering new patterns
  • Informing and enriching analytics

The following steps form the threat-hunting loop:

You can evaluate the maturity of your threat-hunting program by selecting a level from the following:

  • Level 1: Initial (little or no data collection, relying on automated alerts)
  • Level 2: Minimal (high level of data collection)
  • Level 3: Procedural (high level of data collection, following data analysis procedures)
  • Level 4: Innovative (high level of data collection, following new data analysis...
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