Machine Learning for Networking: 5th International Conference, MLN 2022, Paris, France, November 28–30, 2022, Revised Selected Papers

Author:   Éric Renault ,  Paul Mühlethaler
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2023
Volume:   13767
ISBN:  

9783031361821


Pages:   180
Publication Date:   07 July 2023
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Machine Learning for Networking: 5th International Conference, MLN 2022, Paris, France, November 28–30, 2022, Revised Selected Papers


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Overview

This book constitutes the post-conference proceedings of the 5th International Conference on Machine Learning for Networking, MLN 2022, held in Paris, France, November 28–30, 2022. The 12 full papers presented in this book were carefully reviewed and selected from 27 submissions. The papers present novel ideas, results, experiences and work-in-process on all aspects of Machine Learning and Networking.

Full Product Details

Author:   Éric Renault ,  Paul Mühlethaler
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2023
Volume:   13767
Weight:   0.302kg
ISBN:  

9783031361821


ISBN 10:   3031361822
Pages:   180
Publication Date:   07 July 2023
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Comparison of AI-based algorithms for low energy communication.- Development of an Intent-Based Network incorporating Machine Learning for service Assurance of E-commerce Online Stores.- Cyber-attack proactive defense using multivariate time series and machine learning with Fuzzy Inference-based Decision System.- iPerfOPS: a Tool for Machine Learning-Based Optimization through Protocol Selection.- GRAPHSEC -- Advancing the Application of AI/ML to Network Security through Graph Neural Networks.- Low Complexity Adaptive ML Approaches for End-to-End Latency Prediction.- TDMA-based MAC protocols designed or optimized using Artificial Intelligence for safety data dissemination in Vehicular ad-hoc network: A Survey.- A Machine Learning Based Approach to Detect Stealthy Cobalt Strike C\&C Activities from Encrypted Network Traffic.- Unified Emulation-Simulation Training Environment for Autonomous Cyber Agents.- Deep Learning Based Camera Switching for Sports Broadcasting.- Phisherman: Phishing Link Scanner.- Leader-Assisted Client Selection for Federated Learning in Iot via the Cooperation of Nearby Devices.  

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