
Leveraging Artificial Intelligence (AI) Competencies for Next-Generation Cybersecurity Solutions
- 580 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Leveraging Artificial Intelligence (AI) Competencies for Next-Generation Cybersecurity Solutions
About this book
Modern enterprises are facing growing cybersecurity issues due to the massive volume of security-related data they generate over time. AI systems can be developed to resolve a range of these issues with comparative ease. This new book describes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help eliminate them.
With chapters from industry and security experts, this volume discribes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help elimintate them. With chapters from industry and security experts, this volume discusses the many new and emerging AI technologies and approaches that can be harnessed to combat cyberattacks, including big data analytics techniques, deep neural networks, cloud computer networks, convolutional neural networks, IoT edge devices, machine learning approaches, deep learning, blockchain technology, convolutional neural networks, and more.
Some unique features of this book include:
- Detailed overview of various security analytics techniques and tools
- Comprehensive descriptions of the emerging and evolving aspects of artificial intelligence (AI) technologies
- Industry case studies for practical comprehension and application
This book, Leveraging the Artificial Intelligence Competencies for Next-Generation Cybersecurity Solutions, illustrates how AI is a futuristic and flexible technology that can be effectively used for tackling the growing menace of cybercriminals. It clearly demystifies the unique contributions of AI algorithms, models, frameworks, and libraries in nullifying the cyberattacks. The volume will be a valuable resource for research students, scholars, academic professors, business executives, security architects, and consultants in the IT industry.
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Information
Table of contents
- Cover Page
- Half Title page
- Title Page
- Copyright Page
- About the Editors
- Contents
- Contributors
- Preface
- 1 Network Security Risks and Solutions Through Automated Toolkits in Underwater Sensor Network: A Survey
- 2 IoT Security: Challenges, Best Practices, and Service Platforms
- 3 A Fundamental Overview in Cybersecurity: Prevention and Mitigation of Cyberattacks for Securing Cyberspace
- 4 A Review of Big Data Analytics Techniques to Collar Cybersecurity Concerns
- 5 Deep Neural Networks for Automated Cyber Security: Identification of Dynamic Malware in Cloud Computer Networks
- 6 Artificial Intelligence Models for Cyber Security
- 7 Demystifying Digital Transformation Technologies and Tools
- 8 Big Data Analytics in Cyber Threats and Artificial Intelligence
- 9 Cyber Security-Based Solutions for IoT Edge Devices: Critical Issues and Services
- 10 A Structural Framework for Modeling Multi-Stage Network Attacks
- 11 Artificial Intelligence Techniques for Malicious Domain Detection in Cyberspace
- 12 Malicious Domains Detection Based on Machine Learning Techniques
- 13 Use of Artificial Intelligence and the Thread Detection Method in Cyber Security
- 14 The Impact of AI on Cybersecurity in Sustainable Universal Healthcare: Current Developments, Issues, and Future Prospects
- 15 Delineating the Critical Cloud Infrastructure, Application, and Data for Business Agility and Reliability
- 16 Machine Learning Approaches for Dynamic Cyber Security
- 17 Cyber Security in Deep Learning: Challenges and Applications
- 18 Revolution of Digital Transformation Technology: Artificial Intelligence and Blockchain Technology in Cyber Security
- 19 A Survey of Deep Learning Algorithms and Methods for Automated Cyber Security in Healthcare
- 20 An Intrusion Detection System Using the NSL-KDD Dataset's Convolutional Neural Network and Data Analytics
- 21 Cyber Security Through Big Data Analytics
- Index