Computational Intelligence for Cybersecurity Management and Applications

Computational Intelligence for Cybersecurity Management and Applications

by Yassine Maleh, Mamoun Alazab, Soufyane Mounir
Released April 2023
Publisher(s): CRC Press
ISBN: 9781000853414

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Book description

As cyberattacks continue to grow in complexity and number, computational intelligence is helping under-resourced security analysts stay one step ahead of threats. Drawing on threat intelligence from millions of studies, blogs, and news articles, computational intelligence techniques such as machine learning and automatic natural language processing quickly provide the means to identify real threats and dramatically reduce response times.

The book collects and reports on recent high-quality research addressing different cybersecurity challenges. It:

  • explores the newest developments in the use of computational intelligence and AI for cybersecurity applications

  • provides several case studies related to computational intelligence techniques for cybersecurity in a wide range of applications (smart health care, blockchain, cyber-physical system, etc.)

  • integrates theoretical and practical aspects of computational intelligence for cybersecurity so that any reader, from novice to expert, may understand the book’s explanations of key topics.

It offers comprehensive coverage of the essential topics, including:

  • machine learning and deep learning for cybersecurity

  • blockchain for cybersecurity and privacy

  • security engineering for cyber-physical systems

  • AI and data analytics techniques for cybersecurity in smart systems

  • trust in digital systems

This book discusses the current state-of-the-art and practical solutions for the following cybersecurity and privacy issues using artificial intelligence techniques and cutting-edge technology. Readers interested in learning more about computational intelligence techniques for cybersecurity applications and management will find this book invaluable. They will get insight into potential avenues for future study on these topics and be able to prioritize their efforts better.

Table of contents

  1. Cover
  2. Half Title
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Contents
  7. Preface
  8. Editor biographies
  9. Contributors
  10. Section I: Big Data and Computational Intelligence for Cybersecurity Management and Applications
    1. Chapter 1 Big Data and Blockchain for Cybersecurity Applications: Challenges and Solutions
      1. 1.1 Introduction
      2. 1.2 Benefits of Big Data Analytics for Manufacturing Internet of Things
      3. 1.3 Big Data Analytics Research in IoT: Issues and Challenges
      4. 1.4 Computational Intelligence Techniques
      5. 1.5 Integration of Big Data with Business Intelligence
      6. 1.6 Bitcoin Adoption and Rejection
      7. 1.7 Blockchain in Cybersecurity
      8. 1.8 Cyber Security Attacks in Blockchain
      9. 1.9 Use cases of Blockchain in Cybersecurity
      10. 1.10 Integration of Big Data and Blockchain
      11. 1.11 Conclusion
      12. References
    2. Chapter 2 Deep Learning Techniques for Cybersecurity Applications
      1. 2.1 Introduction
      2. 2.2 Artificial Intelligence with Machine Learning and Deep Learning
      3. 2.3 Deep Learning and Neural Network
      4. 2.4 Cybersecurity
      5. 2.5 DL Algorithms for Cybersecurity
      6. 2.6 Cybersecurity Use Cases
      7. 2.7 DL Methods for Cyberattack Detection
      8. 2.8 Cybersecurity Threats and Attacks
      9. 2.9 Conclusion
      10. References
    3. Chapter 3 Deep Learning Techniques for Malware Classification
      1. 3.1 Introduction
      2. 3.2 Related Works
      3. 3.3 Methodology
      4. 3.4 Experiments and Results
      5. 3.5 Conclusion and Future Work
      6. References
  11. Section II: Computational Intelligence for Cybersecurity Applications
    1. Chapter 4 Machine Learning and Blockchain for Security Management in Banking System
      1. 4.1 Introduction
      2. 4.2 Background and Related Works
      3. 4.3 Blockchain and Its Benefits in Banking and Finance
      4. 4.4 Machine Learning–Based Secure Transaction Processing Systems
      5. 4.5 Integration of ML and Blockchain
      6. 4.6 The Proposed Framework
      7. 4.7 Future Research Directions
      8. 4.8 Conclusion
      9. References
    2. Chapter 5 Machine Learning Techniques for Fault Tolerance Management
      1. 5.1 Introduction
      2. 5.2 Related Work
      3. 5.3 System Architecture
      4. 5.4 Result Analysis
      5. 5.5 Conclusions
      6. References
    3. Chapter 6 An Efficient Approach for Image Detection and Recognition Using Artificial Intelligence in Cyber-Physical Systems
      1. 6.1 Introduction
      2. 6.2 Literature Review
      3. 6.3 Research Methodology
      4. 6.4 HAAR Cascade Classifier
      5. 6.5 System Implementation
      6. 6.6 Training Data Preparation
      7. 6.7 Training the Face Recognizer
      8. 6.8 Predicting Faces
      9. 6.9 Test Result Analysis
      10. 6.10 Efficiency Comparison
      11. 6.11 Conclusion
      12. References
  12. Section III: Blockchain and Computational Intelligence for Cybersecurity Applications
    1. Chapter 7 Artificial Intelligence Incorporated in Business Analytics and Blockchain to Enhance Security
      1. 7.1 Introduction
      2. 7.2 Literature Study
      3. 7.3 Application of Artificial Intelligence in Business Analytics
      4. 7.4 Blockchain Technology and the Use of AI
      5. 7.5 Transactions in Blockchain
      6. 7.6 Proof of Work in Blockchain
      7. 7.7 Case Study on AI Using Blockchain
      8. 7.8 AI in Smart Contracts and Its Testing
      9. 7.9 Conclusion
      10. References
    2. Chapter 8 Blockchain Solutions for Security and Privacy Issues in Smart Health Care
      1. 8.1 Introduction
      2. 8.2 Smart Health Care
      3. 8.3 Security and Privacy Requirements of Smart Health Care
      4. 8.4 Security and Privacy Issues in Smart Health Care
      5. 8.5 Blockchain Use Cases in Smart Health Care
      6. 8.6 Blockchain's Role in the Mitigation of Security and Privacy Issues in the Smart Healthcare System
      7. 8.7 Smart Health Care and Computational Intelligence
      8. 8.8 Conclusion
      9. References
    3. Chapter 9 AIC Algorithm for Trust Management in eWOM for Digital Systems
      1. 9.1 Introduction
      2. 9.2 Research Model and Hypothesis
      3. 9.3 Method
      4. 9.4 Results
      5. 9.5 Conclusions
      6. Acknowledgments
      7. References
    4. Chapter 10 Study of IoT Security for Blockchain Management: An Application to Data Backup
      1. 10.1 Introduction
      2. 10.2 Related Works
      3. 10.3 Theoretical Background on IoT
      4. 10.4 Securing the Internet of Things
      5. 10.5 Blockchain-Based Architecture for Securing Data Storage
      6. 10.6 Experiments, Results, and Discussions
      7. 10.7 Conclusion
      8. References
    5. Chapter 11 Cybersecurity Management in Cyber-Physical Systems Using Blockchain
      1. 11.1 Introduction
      2. 11.2 Blockchain (BC) for Cyber-Physical Systems (CPS) Applications
      3. 11.3 Blockchain Applications in Cybersecurity
      4. 11.4 Blockchain Limitations and Future Directions
      5. 11.5 Conclusion
      6. References
  13. Index

Product information

  • Title: Computational Intelligence for Cybersecurity Management and Applications
  • Author(s): Yassine Maleh, Mamoun Alazab, Soufyane Mounir
  • Release date: April 2023
  • Publisher(s): CRC Press
  • ISBN: 9781000853414