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.

Table of Contents

Deep Learning in traffic management: Deep traffic analysis of secure DNS

MINAL MOHARIR, NIKITHA SRIKANTH, NEEL BHANDARI AND RISHA DASSI

Machine Learning based Approach for Detecting Beacon Forgeries in Wi-Fi NetworksROHIT JAYSANKAR, VAMSHI SUNKU MOHAN, AND SRIRAM SANKARAN

Reinforcement learning-based approach towards switch migration for load balancing in SDN

ABHA KUMARI, SHUBHAM GUPTA, JOYDEEP CHANDRA, AND ASHOK SINGH SAIRAM

Green Corridor over a Narrow Lane: Supporting High Priority Message Delivery through NB-IoT

RAJA KARMAKAR, SAMIRAN CHATTOPADHYAY, AND SANDIP CHAKRABORTY

Vulnerabilities Detection in Cyber Security using Deep Learning based Information Security and Event Management

KOTHANDARAMAN D, S SHIVA PRASAD, AND P SIVASANKAR

Detection and Localization of Double Compressed Forged Regions in JPEG Images using DCT Coefficients and Deep Learning based CNN

JAMIMAMUL BAKAS, AND RUCHIRA NASKAR

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