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Artificial Intelligence for Cybersecurity
Artificial Intelligence for Cybersecurity

Artificial Intelligence for Cybersecurity: Develop AI approaches to solve cybersecurity problems in your organization

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Profile Icon Bojan Kolosnjaji Profile Icon Apostolis Zarras Profile Icon Peng Xu Profile Icon Huang Xiao
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£17.99 £26.99
eBook Oct 2024 358 pages 1st Edition
eBook
£17.99 £26.99
Paperback
£33.99
Subscription
Free Trial
Renews at £16.99p/m
Arrow left icon
Profile Icon Bojan Kolosnjaji Profile Icon Apostolis Zarras Profile Icon Peng Xu Profile Icon Huang Xiao
Arrow right icon
£17.99 £26.99
eBook Oct 2024 358 pages 1st Edition
eBook
£17.99 £26.99
Paperback
£33.99
Subscription
Free Trial
Renews at £16.99p/m
eBook
£17.99 £26.99
Paperback
£33.99
Subscription
Free Trial
Renews at £16.99p/m

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Artificial Intelligence for Cybersecurity

Part 1: Data-Driven Cybersecurity and AI

This part introduces how big data technology and AI are changing how we solve problems in cybersecurity. It describes the role of data and automation, as well as the opportunities that collecting large-scale data brings. Furthermore, it enumerates the cybersecurity tools and approaches where big data analytics is already making a difference.

This part has the following chapters:

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Key benefits

  • Familiarize yourself with AI methods and approaches and see how they fit into cybersecurity
  • Learn how to design solutions in cybersecurity that include AI as a key feature
  • Acquire practical AI skills using step-by-step exercises and code examples
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

Artificial intelligence offers data analytics methods that enable us to efficiently recognize patterns in large-scale data. These methods can be applied to various cybersecurity problems, from authentication and the detection of various types of cyberattacks in computer networks to the analysis of malicious executables. Written by a machine learning expert, this book introduces you to the data analytics environment in cybersecurity and shows you where AI methods will fit in your cybersecurity projects. The chapters share an in-depth explanation of the AI methods along with tools that can be used to apply these methods, as well as design and implement AI solutions. You’ll also examine various cybersecurity scenarios where AI methods are applicable, including exercises and code examples that’ll help you effectively apply AI to work on cybersecurity challenges. The book also discusses common pitfalls from real-world applications of AI in cybersecurity issues and teaches you how to tackle them. By the end of this book, you’ll be able to not only recognize where AI methods can be applied, but also design and execute efficient solutions using AI methods.

Who is this book for?

This book is for machine learning practitioners looking to apply their skills to overcome cybersecurity challenges. Cybersecurity workers who want to leverage machine learning methods will also find this book helpful. Fundamental concepts of machine learning and beginner-level knowledge of Python programming are needed to understand the concepts present in this book. Whether you’re a student or an experienced professional, this book offers a unique and valuable learning experience that will enable you to protect your network and data against the ever-evolving threat landscape.

What you will learn

  • Recognize AI as a powerful tool for intelligence analysis of cybersecurity data
  • Explore all the components and workflow of an AI solution
  • Find out how to design an AI-based solution for cybersecurity
  • Discover how to test various AI-based cybersecurity solutions
  • Evaluate your AI solution and describe its advantages to your organization
  • Avoid common pitfalls and difficulties when implementing AI solutions

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 31, 2024
Length: 358 pages
Edition : 1st
Language : English
ISBN-13 : 9781805123552
Category :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want

Product Details

Publication date : Oct 31, 2024
Length: 358 pages
Edition : 1st
Language : English
ISBN-13 : 9781805123552
Category :

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Table of Contents

26 Chapters
Part 1: Data-Driven Cybersecurity and AI Chevron down icon Chevron up icon
Chapter 1: Big Data in Cybersecurity Chevron down icon Chevron up icon
Chapter 2: Automation in Cybersecurity Chevron down icon Chevron up icon
Chapter 3: Cybersecurity Data Analytics Chevron down icon Chevron up icon
Part 2: AI and Where It Fits In Chevron down icon Chevron up icon
Chapter 4: AI, Machine Learning, and Statistics - A Taxonomy Chevron down icon Chevron up icon
Chapter 5: AI Problems and Methods Chevron down icon Chevron up icon
Chapter 6: Workflow, Tools, and Libraries in AI Projects Chevron down icon Chevron up icon
Part 3: Applications of AI in Cybersecurity Chevron down icon Chevron up icon
Chapter 7: Malware and Network Intrusion Detection and Analysis Chevron down icon Chevron up icon
Chapter 8: User and Entity Behavior Analysis Chevron down icon Chevron up icon
Chapter 9: Fraud, Spam, and Phishing Detection Chevron down icon Chevron up icon
Chapter 10: User Authentication and Access Control Chevron down icon Chevron up icon
Chapter 11: Threat Intelligence Chevron down icon Chevron up icon
Chapter 12: Anomaly Detection in Industrial Control Systems Chevron down icon Chevron up icon
Chapter 13: Large Language Models and Cybersecurity Chevron down icon Chevron up icon
Part 4: Common Problems When Applying AI in Cybersecurity Chevron down icon Chevron up icon
Chapter 14: Data Quality and its Usage in the AI and LLM Era Chevron down icon Chevron up icon
Chapter 15: Correlation, Causation, Bias, and Variance Chevron down icon Chevron up icon
Chapter 16: Evaluation, Monitoring, and Feedback Loop Chevron down icon Chevron up icon
Chapter 17: Learning in a Changing and Adversarial Environment Chevron down icon Chevron up icon
Chapter 18: Privacy, Accountability, Explainability, and Trust – Responsible AI Chevron down icon Chevron up icon
Part 5: Final Remarks and Takeaways Chevron down icon Chevron up icon
Chapter 19: Summary Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
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