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  • Book Overview & Buying Artificial Intelligence for Cybersecurity
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Artificial Intelligence for Cybersecurity

Artificial Intelligence for Cybersecurity

By : Bojan Kolosnjaji, Huang Xiao, Peng Xu, Apostolis Zarras
4.3 (4)
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Artificial Intelligence for Cybersecurity

Artificial Intelligence for Cybersecurity

4.3 (4)
By: Bojan Kolosnjaji, Huang Xiao, Peng Xu, Apostolis Zarras

Overview of this book

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. *Email sign-up and proof of purchase required
Table of Contents (27 chapters)
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1
Part 1: Data-Driven Cybersecurity and AI
5
Part 2: AI and Where It Fits In
9
Part 3: Applications of AI in Cybersecurity
17
Part 4: Common Problems When Applying AI in Cybersecurity
23
Part 5: Final Remarks and Takeaways

Preface

The cybersecurity threat landscape is evolving to include an increasing volume and variety of attacks. However, at the same time, the big data era and the proliferation of AI enable new methods and tools to tackle the challenge of detecting increasingly sophisticated malicious activity using large-scale data processing and AI for pattern recognition and enhanced data analytics. AI has already revolutionized multiple areas, some of the most well-known being healthcare, finance, and manufacturing. Currently, AI is making its way into cybersecurity as well through exciting and valuable applications.

In this book, we introduce the place of AI as a methodology in cybersecurity and how AI methods can help solve cybersecurity problems. We give a foundational knowledge of AI for those of you who are beginners in this area, starting with a theoretical underpinning. Following the theoretical chapters, we expand by looking at eight different application areas with six chapters dedicated to these applications. This way, we provide you with practical skills that can be used in concrete scenarios in real-world cybersecurity. After going through these chapters, you can immediately provide value to your organizations or advise your colleagues on how to make a difference with AI in cybersecurity.

Apart from describing the AI methods and going through various application scenarios, we include a part of the book with common pitfalls and challenges in applying AI for cybersecurity. This part helps you to be prepared for real-world applications of AI and the problems that are often overlooked by untrained practitioners, leading to inaccurate project planning and wasted time and effort. We help you recognize those problems and challenges and successfully overcome them to optimize the advantages you get with AI applications.

This book is authored by researchers with years of academic and practical experience applying AI in cybersecurity in various organizations. Publishing this book enables us to share our knowledge and experience in this area to train new experts and help improve cybersecurity overall. The combination of theoretical base and practical skills provided through this book is what has proven to be crucial in successful AI projects!

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