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Advances in information security, privacy, and ethics (AISPE) book series.
Applications of machine learning and deep learning for privacy and cybersecurity / Victor Lobo, Anacleto Correia. — 1 online resource (xxi, 271 pages) : illustrations (chiefly color). — (Advances in information security, privacy, and ethics (AISPE) book series). — <URL:http://elib.fa.ru/ebsco/3380199.pdf>.

Record create date: 11/4/2021

Subject: Computer networks — Security measures — Data processing.; Computer security.; Deep learning (Machine learning); Computer security.; Deep learning (Machine learning)

Collections: EBSCO

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"This comprehensive and timely book provides an overview of the field of Machine and Deep Learning in the areas of cybersecurity and privacy, followed by an in-depth view of emerging research exploring the theoretical aspects of machine and deep learning, as well as real-world implementations"--.

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Table of Contents

  • Cover
  • Title Page
  • Copyright Page
  • Book Series
  • Table of Contents
  • Detailed Table of Contents
  • Preface
  • Chapter 1: User Profiling Using Keystroke Dynamics and Rotation Forest
  • Chapter 2: Predictive Modelling for Financial Fraud Detection Using Data Analytics
  • Chapter 3: Comprehensive Overview of Autonomous Vehicles and Their Security Against DDoS Attacks
  • Chapter 4: Application of Machine Learning to User Behavior-Based Authentication in Smartphone and Web
  • Chapter 5: The Role of Deception in Securing Our Cyberspace
  • Chapter 6: Holistic View on Detecting DDoS Attacks Using Machine Learning
  • Chapter 7: Masked Transient Effect Ring Oscillator Physical Unclonable Function Against Machine Learning Attacks
  • Chapter 8: Detecting Bank Financial Fraud in South Africa Using a Logistic Model Tree
  • Chapter 9: Innovative Legitimate Non-Traditional Doctorate Programs in Cybersecurity, Engineering, and Technology
  • Chapter 10: Privacy Preservation of Image Data With Machine Learning
  • Compilation of References
  • Related References
  • About the Contributors
  • Index

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