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

Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science ; 13767Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edition: 1st ed. 2023Description: X, 180 p. 91 illus., 59 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031361838
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.312 23
LOC classification:
  • QA76.9.D343
Online resources:
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. .
In: Springer Nature eBookSummary: 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.
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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. .

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.

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