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Full Description
Gain well-rounded knowledge of AI methods in cybersecurity and obtain hands-on experience in implementing them to bring value to your organization
Key Features
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
Book DescriptionArtificial 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.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
Who this book is forThis 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.
Contents
Table of Contents
Big Data in Cybersecurity
Automation in Cybersecurity
Cybersecurity Data Analytics
AI, Machine Learning, and Statistics - A Taxonomy
AI Problems and Methods
Workflow, Tools, and Libraries in AI Projects
Malware and Network Intrusion Detection and Analysis
User and Entity Behavior Analysis
Fraud, Spam, and Phishing Detection
User Authentication and Access Control
Threat Intelligence
Anomaly Detection in Industrial Control Systems
Large Language Models and Cybersecurity
Data Quality and Its Usage in the AI and LLM Era
Correlation, Causation, Bias, and Variance
Evaluation, Monitoring, and Feedback Loop
Learning in a Changing and Adversarial Environment
Privacy, Accountability, Explainability, and Trust - Responsible AI
Summary
