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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>.Дата создания записи: 13.08.2019 Тематика: Computer networks — Security measures.; Computer security — Data processing.; Computer crimes — Prevention — Data processing.; Machine learning. Коллекции: EBSCO Разрешенные действия: –
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Группа: Анонимные пользователи Сеть: Интернет |
Аннотация
"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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Интернет | Анонимные пользователи |
Оглавление
- 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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