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Handbook of research on machine and deep learning applications for cyber security / Padmavathi Ganapathi and D. Shanmugapriya, editors. — 1 online resource (482 pages) — <URL:http://elib.fa.ru/ebsco/2227914.pdf>.

Record create date: 8/13/2019

Subject: Computer networks — Security measures.; Computer security — Data processing.; Computer crimes — Prevention — Data processing.; Machine learning.

Collections: EBSCO

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"This book explores the use of machine learning and deep learning applications in the areas of cyber security and cyber-attack handling mechanisms"--.

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Table of Contents

  • Cover
  • Title Page
  • Copyright Page
  • Book Series
  • List of Contributors
  • Table of Contents
  • Detailed Table of Contents
  • Foreword
  • Preface
  • Acknowledgment
  • Chapter 1: Review on Intelligent Algorithms for Cyber Security
  • Chapter 2: A Review on Cyber Security Mechanisms Using Machine and Deep Learning Algorithms
  • Chapter 3: Review on Machine and Deep Learning Applications for Cyber Security
  • Chapter 4: Applications of Machine Learning in Cyber Security Domain
  • Chapter 5: Applications of Machine Learning in Cyber Security
  • Chapter 6: Malware and Anomaly Detection Using Machine Learning and Deep Learning Methods
  • Chapter 7: Cyber Threats Detection and Mitigation Using Machine Learning
  • Chapter 8: Hybridization of Machine Learning Algorithm in Intrusion Detection System
  • Chapter 9: A Hybrid Approach to Detect the Malicious Applications in Android-Based Smartphones Using Deep Learning
  • Chapter 10: Anomaly-Based Intrusion Detection
  • Chapter 11: Traffic Analysis of UAV Networks Using Enhanced Deep Feed Forward Neural Networks (EDFFNN)
  • Chapter 12: A Novel Biometric Image Enhancement Approach With the Hybridization of Undecimated Wavelet Transform and Deep Autoencoder
  • Chapter 13: A 3D-Cellular Automata-Based Publicly-Verifiable Threshold Secret Sharing
  • Chapter 14: Big Data Analytics for Intrusion Detection
  • Chapter 15: Big Data Analytics With Machine Learning and Deep Learning Methods for Detection of Anomalies in Network Traffic
  • Chapter 16: A Secure Protocol for High-Dimensional Big Data Providing Data Privacy
  • Chapter 17: A Review of Machine Learning Methods Applied for Handling Zero-Day Attacks in the Cloud Environment
  • Chapter 18: Adoption of Machine Learning With Adaptive Approach for Securing CPS
  • Chapter 19: Variable Selection Method for Regression Models Using Computational Intelligence Techniques
  • Compilation of References
  • About the Contributors
  • Index

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