
Artificial Intelligence and Deep Learning for Computer Network
Management and Analysis
- 122 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Artificial Intelligence and Deep Learning for Computer Network
Management and Analysis
About this book
Artificial Intelligence and Deep Learning for Computer Network: Management and Analysis aims to systematically collect quality research spanning AI, ML, and deep learning (DL) applications to diverse sub-topics of computer networks, communications, and security, under a single cover. It also aspires to provide more insights on the applicability of the theoretical similitudes, otherwise a rarity in many such books.
Features:
- A diverse collection of important and cutting-edge topics covered in a single volume
- Several chapters on cybersecurity, an extremely active research area
- Recent research results from leading researchers and some pointers to future advancements in methodology
- Detailed experimental results obtained from standard data sets
This book serves as a valuable reference book for students, researchers, and practitioners who wish to study and get acquainted with the application of cutting-edge AI, ML, and DL techniques to network management and cyber security.
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Information
Table of contents
- Cover
- Half Title
- Series Page
- Title Page
- Copyright Page
- Contents
- Preface
- About the Editors
- Contributors
- 1. Deep Learning in Traffic Management: Deep Traffic Analysis of Secure DNS
- 2. Machine LearningāBased Approach for Detecting Beacon Forgeries in Wi-Fi Networks
- 3. Reinforcement LearningāBased Approach Towards Switch Migration for Load-Balancing in SDN
- 4. Green Corridor over a Narrow Lane: Supporting High-Priority Message Delivery through NB-IoT
- 5. Vulnerabilities Detection in Cybersecurity Using Deep LearningāBased Information Security and Event Management
- 6. Detection and Localization of Double-Compressed Forged Regions in JPEG Images Using DCT Coefficients and Deep LearningāBased CNN
- Index
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