Artificial Intelligence and Deep Learning for Computer Network
portes grátis
Artificial Intelligence and Deep Learning for Computer Network
Management and Analysis
Subhra Chakraborty, Rajat; Roy, Sangita; Mazumdar, Arka Prokash; Chakraborty, Sudeshna; Mathew, Jimson
Taylor & Francis Ltd
12/2024
122
Mole
9781032461380
Pré-lançamento - envio 15 a 20 dias após a sua edição
Descrição não disponível.
1. Deep Learning in traffic management: Deep traffic analysis of secure DNS. 2. Machine Learning based Approach for Detecting Beacon Forgeries in Wi-Fi Networks. 3. Reinforcement learning-based 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 Cyber Security using Deep Learning based Information Security and Event Management. 6. Detection and Localization of Double Compressed Forged Regions in JPEG Images using DCT Coefficients and Deep Learning based CNN.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Machine Learning;Optimization;Multimedia;Wireless;MDP;Random Forest;F1 Score;MDP Formulation;IoT Device;JPEG Compression;IoT Network;JPEG Image;JPEG Compress Image;Unbalanced Dataset;Mac Scheduler;Fake Access Points;Balanced Dataset;SDN Controller;CNN Model;Average Throughput;CNN Training;Downlink Scheduling;SDN;Legitimate Access Points;Forgery Detection;SVM Model;Controller Load;SVM Function;Deep Convolutional Neural Network
1. Deep Learning in traffic management: Deep traffic analysis of secure DNS. 2. Machine Learning based Approach for Detecting Beacon Forgeries in Wi-Fi Networks. 3. Reinforcement learning-based 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 Cyber Security using Deep Learning based Information Security and Event Management. 6. Detection and Localization of Double Compressed Forged Regions in JPEG Images using DCT Coefficients and Deep Learning based CNN.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Machine Learning;Optimization;Multimedia;Wireless;MDP;Random Forest;F1 Score;MDP Formulation;IoT Device;JPEG Compression;IoT Network;JPEG Image;JPEG Compress Image;Unbalanced Dataset;Mac Scheduler;Fake Access Points;Balanced Dataset;SDN Controller;CNN Model;Average Throughput;CNN Training;Downlink Scheduling;SDN;Legitimate Access Points;Forgery Detection;SVM Model;Controller Load;SVM Function;Deep Convolutional Neural Network
