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Table of Contents
1 Cover
7 Introduction I.1 Who Is This Book For? I.2 What Is This Book About? I.3 What Is This Book Not About? I.4 Book Organization and Navigation I.5 Glossary of Basic Terms I.6 The Cited NIST Publications I.7 Data and Information Sources Used
8 1 Computer Security with Artificial Intelligence, Machine Learning, and Data Science Combination 1.1 The Current Security Landscape 1.2 Computer Security Basic Concepts 1.3 Sources of Security Threats 1.4 Attacks Against IoT and Wireless Sensor Networks 1.5 Introduction into Artificial Intelligence, Machine Learning, and Data Science 1.6 Fuzzy Logic and Systems 1.7 Machine Learning 1.8 Artificial Neural Networks (ANN) 1.9 Genetic Algorithms (GA) 1.10 Hybrid Intelligent Systems Review Questions Exercises References
9 2 Firewall Design and Implementation 2.1 Firewall Definition, History, and Functions: What Is It? And Where Does It Come From? 2.2 Firewall Operational Models or How Do They Work? 2.3 Basic Firewall Architectures or How Are They Built Up? 2.4 Process of Firewall Design, Implementation, and Maintenance or What Is the Right Way to Put All Things Together? 2.5 Firewall Policy Formalization with Rules or How Is the Knowledge Presented? 2.6 Firewalls Evaluation and Current Developments or How Are They Getting More and More Intelligent? Review Questions Exercises References
10 3 Intrusion Detection Systems 3.1 Definition, Goals, and Primary Functions 3.2 IDS from a Historical Perspective 3.3 Typical IDS Architecture Topologies, Components, and Operational Ranges 3.4 IDS Types: Classification Approaches 3.5 IDS Performance Evaluation 3.6 Artificial Intelligence and Machine Learning Techniques in IDS Design 3.7 Intrusion Detection Challenges and Their Mitigation in IDS Design and Deployment 3.8 Intrusion Detection Tools Review Questions Exercises References Note
11 4 Malware and Vulnerabilities Detection and Protection 4.1 Malware Definition, History, and Trends in Development 4.2 Malware Classification 4.3 Spam 4.4 Software Vulnerabilities 4.5 Principles of Malware Detection and Anti‐malware Protection 4.6 Malware Detection Algorithms 4.7 Anti‐malware Tools Review Questions Exercises References
12 5 Hackers versus Normal Users 5.1 Hacker’s Activities and Protection Against 5.2 Data Science Investigation of Ordinary Users’ Practice 5.3 User’s Authentication 5.4 User’s Anonymity, Attacks Against It, and Protection Review Questions Exercises References
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