Machine Learning for Networking : 4th International Conference, MLN 2021, Virtual Event, December 1-3, 2021, Proceedings / edited by Éric Renault, Selma Boumerdassi, Paul Mühlethaler.

Format:

Book

Contributor:

Renault, Eric, Editor.

Boumerdassi, Selma, Editor.

Mühlethaler, Paul, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Lecture notes in computer science 1611-3349 ; 13175

Lecture Notes in Computer Science, 1611-3349 ; 13175

Language:

English

Subjects (All):

Data mining.

Computer networks.

Application software.

Data Mining and Knowledge Discovery.

Computer Communication Networks.

Computer and Information Systems Applications.

Local Subjects:

Data Mining and Knowledge Discovery.

Computer Communication Networks.

Computer and Information Systems Applications.

Physical Description:

1 online resource (X, 161 pages) : 69 illustrations, 50 illustrations in color.

Edition:

1st ed. 2022.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2022.

System Details:

text file PDF

Summary:

This book constitutes the thoroughly refereed proceedings of the 4th International Conference on Machine Learning for Networking, MLN 2021, held in Paris, France, in December 2021. The 10 revised full papers included in the volume were carefully reviewed and selected from 30 submissions. They present and discuss new trends in in deep and reinforcement learning, pattern recognition and classification for networks, machine learning for network slicing optimization, 5G systems, user behavior prediction, multimedia, IoT, security and protection, optimization and new innovative machine learning methods, performance analysis of machine learning algorithms, experimental evaluations of machine learning, data mining in heterogeneous networks, distributed and decentralized machine learning algorithms, intelligent cloud-support communications, resource allocation, energy-aware communications, software-defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, and underwater sensor networks.

Contents:

Evaluation of Machine Learning Methods for Image Classification: A Case Study of Facility Surface Damage

One-Dimensional Convolutional Neural Network for Detection and Mitigation of DDoS Attacks in SDN

Multi-Armed Bandit-based Channel Hopping: Implementation on Embedded Devices

Cross Inference of Throughput Profiles Using Micro Kernel Network Method

Machine Learning Models for Malicious Traffic Detection in IoT networks /IoT-23 dataset

Application and Mitigation of the Evasion Attack against a Deep Learning Based IDS for Io

DynamicDeepFlow: An Approach for Identifying Changes in Network Traffic Flow Using Unsupervised Clustering

Unsupervised Anomaly Detection using a new Knowledge Graph Model for Network Activity and Events

Deep Reinforcement Learning for Cost-Effective Controller Placement in Software-Defined Multihop Wireless Networking

Distance estimation using LORA and neural networks.

Other Format:

Printed edition:

ISBN:

978-3-030-98978-1

9783030989781

Access Restriction:

Restricted for use by site license.