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Cyber Threat Hunting
Published by Manning
Distributed by Simon & Schuster
Table of Contents
About The Book
Follow the clues, track down the bad actors trying to access your systems, and uncover the chain of evidence left by even the most careful adversary.
Cyber Threat Hunting teaches you how to identify potential breaches of your security. Practical and easy-to-follow, it gives you a reliable and repeatable framework to see and stop attacks.
In Cyber Threat Hunting you will learn how to:
• Design and implement a cyber threat hunting framework
• Think like your adversaries
• Conduct threat hunting expeditions
• Streamline how you work with other cyber security teams
• Structure threat hunting expeditions without losing track of activities and clues
• Use statistics and machine learning techniques to hunt for threats
Organizations that actively seek out security intrusions reduce the time that bad actors spend on their sites, increase their cyber resilience, and build strong resistance to sophisticated covert threats. Cyber Threat Hunting teaches you to recognize attempts to access your systems by seeing the clues your adversaries leave behind. It lays out the path to becoming a successful cyber security threat hunter, guiding you from your very first expedition to hunting in complex cloud-native environments.
Foreword by Anton Chuvakin.
About the technology
Right now, an intruder may be lurking in your network, silently mapping your infrastructure and siphoning off sensitive data. Can you spot the subtle signs? Cyber threat hunting is a security practice aimed at uncovering network and software threats that slip past monitoring and detection systems, and other reactive techniques. In this practical book, author Nadhem AlFardan uses real-world scenarios to help you think like a threat hunter and maximize the success of your expeditions.
About the book
Cyber Threat Hunting teaches you how to conduct structured expeditions using techniques that can detect even the most sophisticated cybersecurity challenges. You’ll begin by mastering the fundamentals: formulating a threat hypothesis, gathering intelligence, strategizing your approach, and executing your hunt. From there, you’ll explore advanced techniques, including machine learning and statistical analysis for anomaly detection. Using this book’s downloadable datasets and scenario templates, you’ll get the hands-on experience you need to refine your threat-hunting expertise.
What's inside
• A threat hunting framework and toolkit
• Think like an adversary
• Effective threat hunting operations
About the reader
For security, network, and systems professionals with some Python experience.
About the author
Nadhem AlFardan, a distinguished architect, leads the Security Operation Center practice team in Cisco Customer Experience, APJC.
Table of Contents
Part 1
1 Introducing threat hunting
2 Building the foundation of a threat-hunting practice
Part 2
3 Your first threat-hunting expedition
4 Threat intelligence for threat hunting
5 Hunting in clouds
Part 3
6 Using fundamental statistical constructs
7 Tuning statistical logic
8 Unsupervised machine learning with k-means
9 Supervised machine learning with Random Forest and XGBoost
10 Hunting with deception
Part 4
11 Responding to findings
12 Measuring success
13 Enabling the team
Appendix A Useful Tools
Cyber Threat Hunting teaches you how to identify potential breaches of your security. Practical and easy-to-follow, it gives you a reliable and repeatable framework to see and stop attacks.
In Cyber Threat Hunting you will learn how to:
• Design and implement a cyber threat hunting framework
• Think like your adversaries
• Conduct threat hunting expeditions
• Streamline how you work with other cyber security teams
• Structure threat hunting expeditions without losing track of activities and clues
• Use statistics and machine learning techniques to hunt for threats
Organizations that actively seek out security intrusions reduce the time that bad actors spend on their sites, increase their cyber resilience, and build strong resistance to sophisticated covert threats. Cyber Threat Hunting teaches you to recognize attempts to access your systems by seeing the clues your adversaries leave behind. It lays out the path to becoming a successful cyber security threat hunter, guiding you from your very first expedition to hunting in complex cloud-native environments.
Foreword by Anton Chuvakin.
About the technology
Right now, an intruder may be lurking in your network, silently mapping your infrastructure and siphoning off sensitive data. Can you spot the subtle signs? Cyber threat hunting is a security practice aimed at uncovering network and software threats that slip past monitoring and detection systems, and other reactive techniques. In this practical book, author Nadhem AlFardan uses real-world scenarios to help you think like a threat hunter and maximize the success of your expeditions.
About the book
Cyber Threat Hunting teaches you how to conduct structured expeditions using techniques that can detect even the most sophisticated cybersecurity challenges. You’ll begin by mastering the fundamentals: formulating a threat hypothesis, gathering intelligence, strategizing your approach, and executing your hunt. From there, you’ll explore advanced techniques, including machine learning and statistical analysis for anomaly detection. Using this book’s downloadable datasets and scenario templates, you’ll get the hands-on experience you need to refine your threat-hunting expertise.
What's inside
• A threat hunting framework and toolkit
• Think like an adversary
• Effective threat hunting operations
About the reader
For security, network, and systems professionals with some Python experience.
About the author
Nadhem AlFardan, a distinguished architect, leads the Security Operation Center practice team in Cisco Customer Experience, APJC.
Table of Contents
Part 1
1 Introducing threat hunting
2 Building the foundation of a threat-hunting practice
Part 2
3 Your first threat-hunting expedition
4 Threat intelligence for threat hunting
5 Hunting in clouds
Part 3
6 Using fundamental statistical constructs
7 Tuning statistical logic
8 Unsupervised machine learning with k-means
9 Supervised machine learning with Random Forest and XGBoost
10 Hunting with deception
Part 4
11 Responding to findings
12 Measuring success
13 Enabling the team
Appendix A Useful Tools
Product Details
- Publisher: Manning (January 28, 2025)
- Length: 416 pages
- ISBN13: 9781638357230
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